llama : fix embeddings #5796

ggerganov · 2024-02-29T13:46:03Z

llama_batch.logits now also indicates if embeddings are output for that token
fix llama_get_embeddings_ith() to return token embeddings
add llama_get_embeddings_seq() to return sequence embeddings
fix embedding example to work both with BERT and non-BERT models
fix server to get the resulting embeddings correctly
add examples/server-embd.py helper script
server supports --pooling

TODO:

rename llama_batch.logits to llama_batch.output (future PR)
BERT graph does not need KV cache - remove it
server should not queue partial prompts when computing embeddings (future PR)

cebtenzzre · 2024-02-29T15:49:01Z

While we're modifying embeddings.cpp - shouldn't this:

struct llama_batch batch = llama_batch_init(n_batch, 0, n_prompts);

be this instead:

struct llama_batch batch = llama_batch_init(n_batch, 0, 1);

Because only one sequence ID is assigned per token?

examples/embedding/embedding.cpp

llama.cpp

tybalex · 2024-02-29T23:16:13Z

should the embeddings from server.cpp get normalized too? embedding.cpp does that.

iamlemec · 2024-03-01T07:45:22Z

Regarding removing the KV cache, I think this will give a big speedup. I did a flamegraph on CUDA, and it was spending fully 50% of the time in calls to llama_kv_cell.has_seq_id for constructing the attention mask in llama_set_inputs. If you know everything is within batch though, you can construct the attention matrix from just the batch object.

ggml-ci

ggerganov · 2024-03-04T09:47:50Z

llama.cpp

+                if (batch.logits[i] == 0) {
+                    continue;
+                }
+                if (hparams.pooling_type == LLAMA_POOLING_TYPE_CLS) {


@iamlemec What is the meaning of CLS in this context? I don't associate this abbreviation with anything

I believe this mode uses the embedding of the CLS token (which is the Bert equivalent of BOS) instead of averaging the embedding of all tokens.

Yeah, always confused me since I think CLoSe, but I guess it stands for (sentence) classification. There's something to be said for replacing it (and the command line flag) with something more expressive like START.

ggml-ci

examples/server-embd.py

llama.cpp

cebtenzzre · 2024-03-04T16:18:06Z

With these changes I'm getting an MSE of 1.3e-3 relative to Sentence Transformers on WikiText with nomic-embed-text-v1.f16.gguf instead of the previous 5.62e-10. Not sure what the problem is.

edit: I'm also still seeing NaNs out of the embedding example.

ggerganov · 2024-03-04T16:22:04Z

With these changes I'm getting an MSE of 1.3e-3 relative to Sentence Transformers on WikiText with nomic-embed-text-v1.f16.gguf instead of the previous 5.62e-10. Not sure what the problem is.

Does it use mean pooling? I think I got it wrong again - checking

cebtenzzre · 2024-03-04T16:25:10Z

Does it use mean pooling?

Yes.

iamlemec · 2024-03-04T16:29:49Z

llama.cpp

+                    case LLAMA_POOLING_TYPE_CLS:
+                        ggml_backend_tensor_get_async(backend_embd, embd, embeddings_out.data() + (n_embd*i), (n_embd*batch.seq_id[i][0])*sizeof(float), n_embd*sizeof(float));
+                        break;
+                    case LLAMA_POOLING_TYPE_MEAN:


We should have the LLAMA_POOLING_TYPE_MEAN case join the LLAMA_POOLING_TYPE_CLS case due to the output order of the averaging matrix.

Yes. I keep getting confused with the sequence-based instead of token-based embedding extraction.

Will try to modify the API to make things more clear

Cool, this change fixes the NaNs from embedding.cpp, and results in the MSE of nomic-embed-text-v1.f16.gguf actually being lower than before (4.71e-10 vs 5.62e-10). Also fp32 is down from 9.34e-11 to 1.18e-14.

Also fp32 is down from 9.34e-11 to 1.18e-14.

This is likely due to no longer going through the KV cache.

Do you have any performance benchmarks to see if this change improved the speed?

ggml-ci

ggerganov · 2024-03-04T17:28:57Z

So I've updated the API to support both sequence and token embeddings:

llama.cpp/llama.h

Lines 657 to 671 in 79e4eed

    
           // Get all output token embeddings 
        
           // shape: [n_tokens*n_embd] (1-dimensional) 
        
           LLAMA_API float * llama_get_embeddings(struct llama_context * ctx); 
        
           // Get the embeddings for the ith token 
        
           // llama_get_embeddings(ctx) + i*n_embd 
        
           // shape: [n_embd] (1-dimensional) 
        
           LLAMA_API float * llama_get_embeddings_ith(struct llama_context * ctx, int32_t i); 
        
           // Get the embeddings for a sequence id 
        
           // Returns NULL if pooling_type is LLAMA_POOLING_TYPE_NONE 
        
           // shape: [n_embd] (1-dimensional) 
        
           LLAMA_API float * llama_get_embeddings_seq(struct llama_context * ctx, llama_seq_id seq_id);

The sequence embeddings (i.e. llama_embeddings_seq()) work only when pooling_type != LLAMA_POOLING_TYPE_NONE, while token embeddings are populated when pooling_type == LLAMA_POOLING_TYPE_NONE. In the future, we can think about adding pooling support for all models (not just BERT) - not sure if it would be useful, but it fits into the implementation logic

With this change, to make the embedding example work with both token and sequence emebeddings (i.e. with and without pooling), we do the following:

llama.cpp/examples/embedding/embedding.cpp

Lines 52 to 65 in fc9af15

    
               // try to get sequence embeddings - supported only when pooling_type is not NONE 
        
               const float * embd = llama_get_embeddings_seq(ctx, batch.seq_id[i][0]); 
        
               if (embd == NULL) { 
        
                   embd = llama_get_embeddings_ith(ctx, i); 
        
                   if (embd == NULL) { 
        
                       fprintf(stderr, "%s: failed to get embeddings for token %d\n", __func__, i); 
        
                       continue; 
        
                   } 
        
               } 
        
               float * out = output + batch.seq_id[i][0] * n_embd; 
        
               normalize(embd, out, n_embd); 
        
           }

First try to get sequence embeddings. This would return NULL if pooling is disabled and we fallback to token embeddings

Hope this finally works. Let me know if you give it a try

ggml-ci

iamlemec · 2024-03-04T20:49:51Z

Working great here! Numbers look very, very similar to earlier.

I'm a little surprised to see a slight performance degredation (around 20-30% on both CPU and CUDA). We're definitely getting gains from the kv-cache attention matrix stuff when that's a factor. But I wonder if it relates to the fact that we're breaking up the final copy into sequences? Either that or one of the smaller changes in built_bert. Looking into it now.

cebtenzzre · 2024-03-04T21:44:44Z

examples/embedding/embedding.cpp

Does the llama_kv_cache_clear still do anything useful?

edit: I remembered that this example is used for models with causal attention as well. I won't need the equivalent if I'm just working with embedding models.

Yes, llama_kv_cache_clear is not necessary for embedding models, but makes sense for causal attention models

* llama : fix embeddings ggml-ci * llama : do not use KV cache for non-causal models ggml-ci * embeddings : fix llama_batch_init arg * llama : add pooling switch * llama : distinguish token vs sequence embeddings ggml-ci * llama : assert pooling tensor * llama : simplify causal mask condition ggml-ci * llama : assert input batch with pooling enabled * readme : update API changes list

ggerganov · 2024-03-05T07:52:25Z

I'm a little surprised to see a slight performance degredation (around 20-30% on both CPU and CUDA). We're definitely getting gains from the kv-cache attention matrix stuff when that's a factor. But I wonder if it relates to the fact that we're breaking up the final copy into sequences? Either that or one of the smaller changes in built_bert. Looking into it now.

Let me know what you find. I guess the embeddings extraction is now indeed a bit slower due to the std::map and loop over the batch. The actual computation seems to be the same speed as before (at least with Metal that is). You can bench it with llama-bench since it does not involve any embeddings extraction.

The main struggle with the API was to find a way to differentiate between token embeddings and sequence embeddings. Without the std::map there was an ambiguity in which embeddings you were extracting. There might be better way to do it though

The big benefit of not using the KV cache is that now we don't need to allocate a large KV cache memory buffer. For example, you can compute 32k token embeddings with just a large enough batch size (e.g. -c 512 -b 32768)

@JohannesGaessler

* fix mul_mat fault in cpy_f32_f16 * rm unused function * add wait() for memcpy * restore ci/run.sh, rename struct defination, fix bug in ggml_sycl_op_mul_mat_sycl * fix format issue * llama : fix segfault from unknown model arch name (#5820) * llama : fix segfault from unknown model arch name * llama : make all LLM maps const This also requires using `std::map::at` instead of its `operator[]` which does not exist for const maps. * llama : name LLM_ARCH_UNKNOWN to "(unknown)" This avoids errors from `std::map::at` when getting the general name of the model architecture. Using "(unknown)" instead of an empty string as per suggestion #5820 (comment) * llama : remove redundant inner const for LLM_TENSOR_NAMES The extra const won't do anything here as const maps return const references to values. Co-authored-by: Jared Van Bortel <cebtenzzre@gmail.com> * llama : remove redundant nullptr check in llm_arch_from_string Since LLM_ARCH_NAMES is a const map, no spurious elements with a NULL name are inserted anymore, so this check is dead code. --------- Co-authored-by: Jared Van Bortel <cebtenzzre@gmail.com> * llama : refactor internal quantization functions (#5830) * scripts : add pod-llama.sh * ggml : IQ3_S improvements (#5829) * iq3_s: somewhat faster AVX2 dot product On Ryzen a 7950X TG-128 increases to 16 t/s from 15.5 t/s using 16 threads. For 8 threads it is 13.85 t/s vs 11.75 t/s. PP-512 increases to 28.5 t/s from 23.8 t/s. * iq3_s: somewhat faster ARM_NEON dot product Still dog slow - 10.7 t/s up from 9.9 t/s. * iq3_s: another small ARM_NEON improvement 10.7 -> 11.0 t/s. Using vmulq_s8 is faster than the xor - sub trick that works best on AVX2. * iq3_s: minor improvement on Metal 49.4 t/s -> 50.3 t/s * iq3_s: PPL improvement E.g., for a context of 4096 LLaMA-v2-7B goes to 5.1340 from 5.1653. * iq3_s: use new grid everywhere * Fix ARM_NEON --------- Co-authored-by: Iwan Kawrakow <iwan.kawrakow@gmail.com> * convert-hf : make model class definitions self-contained (#5825) * convert : automatically fall back to HfVocab if tokenizer.model doesn't exist (#5821) * ggml : fix IQ3_S AVX implementation (#5834) ggml-ci * llama : add abort_callback to interrupt computation (#5409) * using abort_callback from ggml to stop llama computation * format fix * a brief explaining comment --------- Co-authored-by: Georgi Gerganov <ggerganov@gmail.com> * server: tests: passkey challenge / self-extend with context shift demo (#5832) * server: tests: add models endpoint scenario * server: /v1/models add some metadata * server: tests: add debug field in context before scenario * server: tests: download model from HF, add batch size * server: tests: add passkey test * server: tests: add group attention params * server: do not truncate prompt tokens if self-extend through group attention is enabled * server: logs: do not truncate log values * server: tests - passkey - first good working value of nga * server: tests: fix server timeout * server: tests: fix passkey, add doc, fix regex content matching, fix timeout * server: tests: fix regex content matching * server: tests: schedule slow tests on master * server: metrics: fix when no prompt processed * server: tests: self-extend add llama-2-7B and Mixtral-8x7B-v0.1 * server: tests: increase timeout for completion * server: tests: keep only the PHI-2 test * server: tests: passkey add a negative test * flake.lock: Update (#5842) Flake lock file updates: • Updated input 'flake-parts': 'github:hercules-ci/flake-parts/b253292d9c0a5ead9bc98c4e9a26c6312e27d69f' (2024-02-01) → 'github:hercules-ci/flake-parts/f7b3c975cf067e56e7cda6cb098ebe3fb4d74ca2' (2024-03-01) • Updated input 'flake-parts/nixpkgs-lib': 'github:NixOS/nixpkgs/97b17f32362e475016f942bbdfda4a4a72a8a652?dir=lib' (2024-01-29) → 'github:NixOS/nixpkgs/1536926ef5621b09bba54035ae2bb6d806d72ac8?dir=lib' (2024-02-29) • Updated input 'nixpkgs': 'github:NixOS/nixpkgs/cbc4211f0afffe6dfd2478a62615dd5175a13f9a' (2024-02-23) → 'github:NixOS/nixpkgs/1536926ef5621b09bba54035ae2bb6d806d72ac8' (2024-02-29) Co-authored-by: github-actions[bot] <github-actions[bot]@users.noreply.github.com> * server : init http requests thread pool with --parallel if set (#5836) * ci : schedule slow server tests only on Release or on demand (#5839) * llama : fix llama_copy_state_data with fragmented KV cache (#5840) The row size of the saved states was based on kv_self.head while it should be based on llama_kv_cache_cell_max. Existing session files should still work. * llama : fix llama_kv_cache_cell_max inability to return 1 I've also changed its return type to uint32_t, because this function is always used to set the value of uint32_t variables, and because the index already has this type. * llama : fix state size calculation Some bytes in the state were unaccounted for in llama_get_state_size. Since the logits reserve so much space, it did not cause problems. * gguf-dump : support i-quants (#5841) Co-authored-by: Black_Fox <radekliska@gmail.com> * llama : allow for user specified embedding pooling type (#5849) * allow for user specified pooling type * llama : use enum types over int --------- Co-authored-by: Georgi Gerganov <ggerganov@gmail.com> * readme : add API changes section * cuda : fix data race in soft max (#5853) * main : support special tokens as reverse/anti prompt (#5847) * Support special tokens as reverse/anti prompt. * Tokenize antiprompts only once. * main : minor --------- Co-authored-by: Georgi Gerganov <ggerganov@gmail.com> * common : use LLAMA_DEFAULT_SEED (#5855) * add some new ops, fix some operators and add batch operations to certain operators. (ggml/747) * cuda: fix group_norm * cuda: add batch inference support for ggml_pad/ggml_upscale * add ggml_arrange * add ggml_timestep_embedding * update ggml_arange/ggml_timestep_embedding tests * cuda: fix im2col * add ggml_arange/ggml_timestep_embbeding support for metal backend * fix some bugs * fix some bugs * Update ggml.h Co-authored-by: Georgi Gerganov <ggerganov@gmail.com> * Update ggml-cuda.cu Co-authored-by: Georgi Gerganov <ggerganov@gmail.com> * Update ggml-metal.m Co-authored-by: Georgi Gerganov <ggerganov@gmail.com> * Update ggml-metal.m Co-authored-by: Georgi Gerganov <ggerganov@gmail.com> * Update ggml-metal.metal Co-authored-by: Georgi Gerganov <ggerganov@gmail.com> * modify according to the review comments * ggml : fix compile warnings + code style * ggml : normalize compute_forward calls + fix seg fault in debug * minor --------- Co-authored-by: Georgi Gerganov <ggerganov@gmail.com> Co-authored-by: slaren <slarengh@gmail.com> * sync : ggml * add alias for chat template (#5858) * speculative : implement stochastic speculative sampling (#5625) * (WIP) Implement stochastic speculative decoding * sample from residual distribution on draft accept failure * fix #5657: force greedy sampling with probs when temp is 0 * remove p_accept parameter * fix style * remove unused variables * add srand() in speculative.cpp * replace use of rand() with mt19937 sampling * fixes based on review (@JohannesGaessler) * fix r random generation * randomly select next sequence to verify + fix bug in memory freeing * fix bug in active_seqs sync * fix uniform int distribution initialization * remove warnings from comparison between int and size_t * check grammar in `llama_sample_probability_distribution_impl` * remove malloc code by utilizing vectors * add PR link to README * cmake : handle cases where git index is not found in .git (#5844) * Update CMakeLists.txt * Update CMakeLists.txt * ggml : introduce ggml_status (ggml/750) * using enum as an exit code instead of macros * update return type from enum to unsigned int * indentation fix * compound update ggml_compute_exit_code -> ggml_status changed ggml_status from a bit-field type to simple codes ggml_status to string cast * ggml_status to string cast * GGML_CALL was removed Co-authored-by: slaren <slarengh@gmail.com> --------- Co-authored-by: slaren <slarengh@gmail.com> Co-authored-by: Georgi Gerganov <ggerganov@gmail.com> * sync : ggml ggml-ci * ggml : fix unknown status (#0) * flake : fix * llama : fix embeddings (#5796) * llama : fix embeddings ggml-ci * llama : do not use KV cache for non-causal models ggml-ci * embeddings : fix llama_batch_init arg * llama : add pooling switch * llama : distinguish token vs sequence embeddings ggml-ci * llama : assert pooling tensor * llama : simplify causal mask condition ggml-ci * llama : assert input batch with pooling enabled * readme : update API changes list * nix: static build (#5814) * fix speculative decoding build on windows (#5874) * rebase and rm tailing space --------- Co-authored-by: LiangtaoJin <liang-tao.jin@intel.com> Co-authored-by: compilade <113953597+compilade@users.noreply.github.com> Co-authored-by: Jared Van Bortel <cebtenzzre@gmail.com> Co-authored-by: Xuan Son Nguyen <thichthat@gmail.com> Co-authored-by: Georgi Gerganov <ggerganov@gmail.com> Co-authored-by: Kawrakow <48489457+ikawrakow@users.noreply.github.com> Co-authored-by: Iwan Kawrakow <iwan.kawrakow@gmail.com> Co-authored-by: Jared Van Bortel <jared@nomic.ai> Co-authored-by: Michael Podvitskiy <podvitskiymichael@gmail.com> Co-authored-by: Pierrick Hymbert <pierrick.hymbert@gmail.com> Co-authored-by: github-actions[bot] <github-actions[bot]@users.noreply.github.com> Co-authored-by: Nindaleth <Nindaleth@users.noreply.github.com> Co-authored-by: Black_Fox <radekliska@gmail.com> Co-authored-by: Douglas Hanley <thesecretaryofwar@gmail.com> Co-authored-by: slaren <slarengh@gmail.com> Co-authored-by: DAN™ <dranger003@gmail.com> Co-authored-by: leejet <leejet714@gmail.com> Co-authored-by: Minsoo Cheong <54794500+mscheong01@users.noreply.github.com> Co-authored-by: Dane Madsen <dane_madsen@hotmail.com> Co-authored-by: hutli <6594598+hutli@users.noreply.github.com> Co-authored-by: Jeffrey Quesnelle <emozilla@nousresearch.com>

iamlemec · 2024-03-05T19:05:52Z

Oh nice, I didn't know about llama-bench. So for CPU I'm seeing ~20% performance drop, not too bad. But for CUDA I'm getting an almost 60% drop:

model	backend	ngl	test	(pre) t/s	(post) t/s
bert 109M F16	CUDA	99	pp 512	177281.98 ± 116298.41	74489.67 ± 19758.33
bert 109M F16	CUDA	0	pp 512	6824.48 ± 1151.24	5556.47 ± 536.14

It seems like the kv cache code relies more on ggml_view_3d instead of contiguous permutes, but I haven't yet found anything that yields the old performance.

ggerganov · 2024-03-05T19:26:03Z

Try #5891 and see if it restores the performance

* llama : fix embeddings ggml-ci * llama : do not use KV cache for non-causal models ggml-ci * embeddings : fix llama_batch_init arg * llama : add pooling switch * llama : distinguish token vs sequence embeddings ggml-ci * llama : assert pooling tensor * llama : simplify causal mask condition ggml-ci * llama : assert input batch with pooling enabled * readme : update API changes list

@JohannesGaessler

* fix mul_mat fault in cpy_f32_f16 * rm unused function * add wait() for memcpy * restore ci/run.sh, rename struct defination, fix bug in ggml_sycl_op_mul_mat_sycl * fix format issue * llama : fix segfault from unknown model arch name (ggerganov#5820) * llama : fix segfault from unknown model arch name * llama : make all LLM maps const This also requires using `std::map::at` instead of its `operator[]` which does not exist for const maps. * llama : name LLM_ARCH_UNKNOWN to "(unknown)" This avoids errors from `std::map::at` when getting the general name of the model architecture. Using "(unknown)" instead of an empty string as per suggestion ggerganov#5820 (comment) * llama : remove redundant inner const for LLM_TENSOR_NAMES The extra const won't do anything here as const maps return const references to values. Co-authored-by: Jared Van Bortel <cebtenzzre@gmail.com> * llama : remove redundant nullptr check in llm_arch_from_string Since LLM_ARCH_NAMES is a const map, no spurious elements with a NULL name are inserted anymore, so this check is dead code. --------- Co-authored-by: Jared Van Bortel <cebtenzzre@gmail.com> * llama : refactor internal quantization functions (ggerganov#5830) * scripts : add pod-llama.sh * ggml : IQ3_S improvements (ggerganov#5829) * iq3_s: somewhat faster AVX2 dot product On Ryzen a 7950X TG-128 increases to 16 t/s from 15.5 t/s using 16 threads. For 8 threads it is 13.85 t/s vs 11.75 t/s. PP-512 increases to 28.5 t/s from 23.8 t/s. * iq3_s: somewhat faster ARM_NEON dot product Still dog slow - 10.7 t/s up from 9.9 t/s. * iq3_s: another small ARM_NEON improvement 10.7 -> 11.0 t/s. Using vmulq_s8 is faster than the xor - sub trick that works best on AVX2. * iq3_s: minor improvement on Metal 49.4 t/s -> 50.3 t/s * iq3_s: PPL improvement E.g., for a context of 4096 LLaMA-v2-7B goes to 5.1340 from 5.1653. * iq3_s: use new grid everywhere * Fix ARM_NEON --------- Co-authored-by: Iwan Kawrakow <iwan.kawrakow@gmail.com> * convert-hf : make model class definitions self-contained (ggerganov#5825) * convert : automatically fall back to HfVocab if tokenizer.model doesn't exist (ggerganov#5821) * ggml : fix IQ3_S AVX implementation (ggerganov#5834) ggml-ci * llama : add abort_callback to interrupt computation (ggerganov#5409) * using abort_callback from ggml to stop llama computation * format fix * a brief explaining comment --------- Co-authored-by: Georgi Gerganov <ggerganov@gmail.com> * server: tests: passkey challenge / self-extend with context shift demo (ggerganov#5832) * server: tests: add models endpoint scenario * server: /v1/models add some metadata * server: tests: add debug field in context before scenario * server: tests: download model from HF, add batch size * server: tests: add passkey test * server: tests: add group attention params * server: do not truncate prompt tokens if self-extend through group attention is enabled * server: logs: do not truncate log values * server: tests - passkey - first good working value of nga * server: tests: fix server timeout * server: tests: fix passkey, add doc, fix regex content matching, fix timeout * server: tests: fix regex content matching * server: tests: schedule slow tests on master * server: metrics: fix when no prompt processed * server: tests: self-extend add llama-2-7B and Mixtral-8x7B-v0.1 * server: tests: increase timeout for completion * server: tests: keep only the PHI-2 test * server: tests: passkey add a negative test * flake.lock: Update (ggerganov#5842) Flake lock file updates: • Updated input 'flake-parts': 'github:hercules-ci/flake-parts/b253292d9c0a5ead9bc98c4e9a26c6312e27d69f' (2024-02-01) → 'github:hercules-ci/flake-parts/f7b3c975cf067e56e7cda6cb098ebe3fb4d74ca2' (2024-03-01) • Updated input 'flake-parts/nixpkgs-lib': 'github:NixOS/nixpkgs/97b17f32362e475016f942bbdfda4a4a72a8a652?dir=lib' (2024-01-29) → 'github:NixOS/nixpkgs/1536926ef5621b09bba54035ae2bb6d806d72ac8?dir=lib' (2024-02-29) • Updated input 'nixpkgs': 'github:NixOS/nixpkgs/cbc4211f0afffe6dfd2478a62615dd5175a13f9a' (2024-02-23) → 'github:NixOS/nixpkgs/1536926ef5621b09bba54035ae2bb6d806d72ac8' (2024-02-29) Co-authored-by: github-actions[bot] <github-actions[bot]@users.noreply.github.com> * server : init http requests thread pool with --parallel if set (ggerganov#5836) * ci : schedule slow server tests only on Release or on demand (ggerganov#5839) * llama : fix llama_copy_state_data with fragmented KV cache (ggerganov#5840) The row size of the saved states was based on kv_self.head while it should be based on llama_kv_cache_cell_max. Existing session files should still work. * llama : fix llama_kv_cache_cell_max inability to return 1 I've also changed its return type to uint32_t, because this function is always used to set the value of uint32_t variables, and because the index already has this type. * llama : fix state size calculation Some bytes in the state were unaccounted for in llama_get_state_size. Since the logits reserve so much space, it did not cause problems. * gguf-dump : support i-quants (ggerganov#5841) Co-authored-by: Black_Fox <radekliska@gmail.com> * llama : allow for user specified embedding pooling type (ggerganov#5849) * allow for user specified pooling type * llama : use enum types over int --------- Co-authored-by: Georgi Gerganov <ggerganov@gmail.com> * readme : add API changes section * cuda : fix data race in soft max (ggerganov#5853) * main : support special tokens as reverse/anti prompt (ggerganov#5847) * Support special tokens as reverse/anti prompt. * Tokenize antiprompts only once. * main : minor --------- Co-authored-by: Georgi Gerganov <ggerganov@gmail.com> * common : use LLAMA_DEFAULT_SEED (ggerganov#5855) * add some new ops, fix some operators and add batch operations to certain operators. (ggml/747) * cuda: fix group_norm * cuda: add batch inference support for ggml_pad/ggml_upscale * add ggml_arrange * add ggml_timestep_embedding * update ggml_arange/ggml_timestep_embedding tests * cuda: fix im2col * add ggml_arange/ggml_timestep_embbeding support for metal backend * fix some bugs * fix some bugs * Update ggml.h Co-authored-by: Georgi Gerganov <ggerganov@gmail.com> * Update ggml-cuda.cu Co-authored-by: Georgi Gerganov <ggerganov@gmail.com> * Update ggml-metal.m Co-authored-by: Georgi Gerganov <ggerganov@gmail.com> * Update ggml-metal.m Co-authored-by: Georgi Gerganov <ggerganov@gmail.com> * Update ggml-metal.metal Co-authored-by: Georgi Gerganov <ggerganov@gmail.com> * modify according to the review comments * ggml : fix compile warnings + code style * ggml : normalize compute_forward calls + fix seg fault in debug * minor --------- Co-authored-by: Georgi Gerganov <ggerganov@gmail.com> Co-authored-by: slaren <slarengh@gmail.com> * sync : ggml * add alias for chat template (ggerganov#5858) * speculative : implement stochastic speculative sampling (ggerganov#5625) * (WIP) Implement stochastic speculative decoding * sample from residual distribution on draft accept failure * fix ggerganov#5657: force greedy sampling with probs when temp is 0 * remove p_accept parameter * fix style * remove unused variables * add srand() in speculative.cpp * replace use of rand() with mt19937 sampling * fixes based on review (@JohannesGaessler) * fix r random generation * randomly select next sequence to verify + fix bug in memory freeing * fix bug in active_seqs sync * fix uniform int distribution initialization * remove warnings from comparison between int and size_t * check grammar in `llama_sample_probability_distribution_impl` * remove malloc code by utilizing vectors * add PR link to README * cmake : handle cases where git index is not found in .git (ggerganov#5844) * Update CMakeLists.txt * Update CMakeLists.txt * ggml : introduce ggml_status (ggml/750) * using enum as an exit code instead of macros * update return type from enum to unsigned int * indentation fix * compound update ggml_compute_exit_code -> ggml_status changed ggml_status from a bit-field type to simple codes ggml_status to string cast * ggml_status to string cast * GGML_CALL was removed Co-authored-by: slaren <slarengh@gmail.com> --------- Co-authored-by: slaren <slarengh@gmail.com> Co-authored-by: Georgi Gerganov <ggerganov@gmail.com> * sync : ggml ggml-ci * ggml : fix unknown status (#0) * flake : fix * llama : fix embeddings (ggerganov#5796) * llama : fix embeddings ggml-ci * llama : do not use KV cache for non-causal models ggml-ci * embeddings : fix llama_batch_init arg * llama : add pooling switch * llama : distinguish token vs sequence embeddings ggml-ci * llama : assert pooling tensor * llama : simplify causal mask condition ggml-ci * llama : assert input batch with pooling enabled * readme : update API changes list * nix: static build (ggerganov#5814) * fix speculative decoding build on windows (ggerganov#5874) * rebase and rm tailing space --------- Co-authored-by: LiangtaoJin <liang-tao.jin@intel.com> Co-authored-by: compilade <113953597+compilade@users.noreply.github.com> Co-authored-by: Jared Van Bortel <cebtenzzre@gmail.com> Co-authored-by: Xuan Son Nguyen <thichthat@gmail.com> Co-authored-by: Georgi Gerganov <ggerganov@gmail.com> Co-authored-by: Kawrakow <48489457+ikawrakow@users.noreply.github.com> Co-authored-by: Iwan Kawrakow <iwan.kawrakow@gmail.com> Co-authored-by: Jared Van Bortel <jared@nomic.ai> Co-authored-by: Michael Podvitskiy <podvitskiymichael@gmail.com> Co-authored-by: Pierrick Hymbert <pierrick.hymbert@gmail.com> Co-authored-by: github-actions[bot] <github-actions[bot]@users.noreply.github.com> Co-authored-by: Nindaleth <Nindaleth@users.noreply.github.com> Co-authored-by: Black_Fox <radekliska@gmail.com> Co-authored-by: Douglas Hanley <thesecretaryofwar@gmail.com> Co-authored-by: slaren <slarengh@gmail.com> Co-authored-by: DAN™ <dranger003@gmail.com> Co-authored-by: leejet <leejet714@gmail.com> Co-authored-by: Minsoo Cheong <54794500+mscheong01@users.noreply.github.com> Co-authored-by: Dane Madsen <dane_madsen@hotmail.com> Co-authored-by: hutli <6594598+hutli@users.noreply.github.com> Co-authored-by: Jeffrey Quesnelle <emozilla@nousresearch.com>

* llama : fix embeddings ggml-ci * llama : do not use KV cache for non-causal models ggml-ci * embeddings : fix llama_batch_init arg * llama : add pooling switch * llama : distinguish token vs sequence embeddings ggml-ci * llama : assert pooling tensor * llama : simplify causal mask condition ggml-ci * llama : assert input batch with pooling enabled * readme : update API changes list

@JohannesGaessler

* fix mul_mat fault in cpy_f32_f16 * rm unused function * add wait() for memcpy * restore ci/run.sh, rename struct defination, fix bug in ggml_sycl_op_mul_mat_sycl * fix format issue * llama : fix segfault from unknown model arch name (ggerganov#5820) * llama : fix segfault from unknown model arch name * llama : make all LLM maps const This also requires using `std::map::at` instead of its `operator[]` which does not exist for const maps. * llama : name LLM_ARCH_UNKNOWN to "(unknown)" This avoids errors from `std::map::at` when getting the general name of the model architecture. Using "(unknown)" instead of an empty string as per suggestion ggerganov#5820 (comment) * llama : remove redundant inner const for LLM_TENSOR_NAMES The extra const won't do anything here as const maps return const references to values. Co-authored-by: Jared Van Bortel <cebtenzzre@gmail.com> * llama : remove redundant nullptr check in llm_arch_from_string Since LLM_ARCH_NAMES is a const map, no spurious elements with a NULL name are inserted anymore, so this check is dead code. --------- Co-authored-by: Jared Van Bortel <cebtenzzre@gmail.com> * llama : refactor internal quantization functions (ggerganov#5830) * scripts : add pod-llama.sh * ggml : IQ3_S improvements (ggerganov#5829) * iq3_s: somewhat faster AVX2 dot product On Ryzen a 7950X TG-128 increases to 16 t/s from 15.5 t/s using 16 threads. For 8 threads it is 13.85 t/s vs 11.75 t/s. PP-512 increases to 28.5 t/s from 23.8 t/s. * iq3_s: somewhat faster ARM_NEON dot product Still dog slow - 10.7 t/s up from 9.9 t/s. * iq3_s: another small ARM_NEON improvement 10.7 -> 11.0 t/s. Using vmulq_s8 is faster than the xor - sub trick that works best on AVX2. * iq3_s: minor improvement on Metal 49.4 t/s -> 50.3 t/s * iq3_s: PPL improvement E.g., for a context of 4096 LLaMA-v2-7B goes to 5.1340 from 5.1653. * iq3_s: use new grid everywhere * Fix ARM_NEON --------- Co-authored-by: Iwan Kawrakow <iwan.kawrakow@gmail.com> * convert-hf : make model class definitions self-contained (ggerganov#5825) * convert : automatically fall back to HfVocab if tokenizer.model doesn't exist (ggerganov#5821) * ggml : fix IQ3_S AVX implementation (ggerganov#5834) ggml-ci * llama : add abort_callback to interrupt computation (ggerganov#5409) * using abort_callback from ggml to stop llama computation * format fix * a brief explaining comment --------- Co-authored-by: Georgi Gerganov <ggerganov@gmail.com> * server: tests: passkey challenge / self-extend with context shift demo (ggerganov#5832) * server: tests: add models endpoint scenario * server: /v1/models add some metadata * server: tests: add debug field in context before scenario * server: tests: download model from HF, add batch size * server: tests: add passkey test * server: tests: add group attention params * server: do not truncate prompt tokens if self-extend through group attention is enabled * server: logs: do not truncate log values * server: tests - passkey - first good working value of nga * server: tests: fix server timeout * server: tests: fix passkey, add doc, fix regex content matching, fix timeout * server: tests: fix regex content matching * server: tests: schedule slow tests on master * server: metrics: fix when no prompt processed * server: tests: self-extend add llama-2-7B and Mixtral-8x7B-v0.1 * server: tests: increase timeout for completion * server: tests: keep only the PHI-2 test * server: tests: passkey add a negative test * flake.lock: Update (ggerganov#5842) Flake lock file updates: • Updated input 'flake-parts': 'github:hercules-ci/flake-parts/b253292d9c0a5ead9bc98c4e9a26c6312e27d69f' (2024-02-01) → 'github:hercules-ci/flake-parts/f7b3c975cf067e56e7cda6cb098ebe3fb4d74ca2' (2024-03-01) • Updated input 'flake-parts/nixpkgs-lib': 'github:NixOS/nixpkgs/97b17f32362e475016f942bbdfda4a4a72a8a652?dir=lib' (2024-01-29) → 'github:NixOS/nixpkgs/1536926ef5621b09bba54035ae2bb6d806d72ac8?dir=lib' (2024-02-29) • Updated input 'nixpkgs': 'github:NixOS/nixpkgs/cbc4211f0afffe6dfd2478a62615dd5175a13f9a' (2024-02-23) → 'github:NixOS/nixpkgs/1536926ef5621b09bba54035ae2bb6d806d72ac8' (2024-02-29) Co-authored-by: github-actions[bot] <github-actions[bot]@users.noreply.github.com> * server : init http requests thread pool with --parallel if set (ggerganov#5836) * ci : schedule slow server tests only on Release or on demand (ggerganov#5839) * llama : fix llama_copy_state_data with fragmented KV cache (ggerganov#5840) The row size of the saved states was based on kv_self.head while it should be based on llama_kv_cache_cell_max. Existing session files should still work. * llama : fix llama_kv_cache_cell_max inability to return 1 I've also changed its return type to uint32_t, because this function is always used to set the value of uint32_t variables, and because the index already has this type. * llama : fix state size calculation Some bytes in the state were unaccounted for in llama_get_state_size. Since the logits reserve so much space, it did not cause problems. * gguf-dump : support i-quants (ggerganov#5841) Co-authored-by: Black_Fox <radekliska@gmail.com> * llama : allow for user specified embedding pooling type (ggerganov#5849) * allow for user specified pooling type * llama : use enum types over int --------- Co-authored-by: Georgi Gerganov <ggerganov@gmail.com> * readme : add API changes section * cuda : fix data race in soft max (ggerganov#5853) * main : support special tokens as reverse/anti prompt (ggerganov#5847) * Support special tokens as reverse/anti prompt. * Tokenize antiprompts only once. * main : minor --------- Co-authored-by: Georgi Gerganov <ggerganov@gmail.com> * common : use LLAMA_DEFAULT_SEED (ggerganov#5855) * add some new ops, fix some operators and add batch operations to certain operators. (ggml/747) * cuda: fix group_norm * cuda: add batch inference support for ggml_pad/ggml_upscale * add ggml_arrange * add ggml_timestep_embedding * update ggml_arange/ggml_timestep_embedding tests * cuda: fix im2col * add ggml_arange/ggml_timestep_embbeding support for metal backend * fix some bugs * fix some bugs * Update ggml.h Co-authored-by: Georgi Gerganov <ggerganov@gmail.com> * Update ggml-cuda.cu Co-authored-by: Georgi Gerganov <ggerganov@gmail.com> * Update ggml-metal.m Co-authored-by: Georgi Gerganov <ggerganov@gmail.com> * Update ggml-metal.m Co-authored-by: Georgi Gerganov <ggerganov@gmail.com> * Update ggml-metal.metal Co-authored-by: Georgi Gerganov <ggerganov@gmail.com> * modify according to the review comments * ggml : fix compile warnings + code style * ggml : normalize compute_forward calls + fix seg fault in debug * minor --------- Co-authored-by: Georgi Gerganov <ggerganov@gmail.com> Co-authored-by: slaren <slarengh@gmail.com> * sync : ggml * add alias for chat template (ggerganov#5858) * speculative : implement stochastic speculative sampling (ggerganov#5625) * (WIP) Implement stochastic speculative decoding * sample from residual distribution on draft accept failure * fix ggerganov#5657: force greedy sampling with probs when temp is 0 * remove p_accept parameter * fix style * remove unused variables * add srand() in speculative.cpp * replace use of rand() with mt19937 sampling * fixes based on review (@JohannesGaessler) * fix r random generation * randomly select next sequence to verify + fix bug in memory freeing * fix bug in active_seqs sync * fix uniform int distribution initialization * remove warnings from comparison between int and size_t * check grammar in `llama_sample_probability_distribution_impl` * remove malloc code by utilizing vectors * add PR link to README * cmake : handle cases where git index is not found in .git (ggerganov#5844) * Update CMakeLists.txt * Update CMakeLists.txt * ggml : introduce ggml_status (ggml/750) * using enum as an exit code instead of macros * update return type from enum to unsigned int * indentation fix * compound update ggml_compute_exit_code -> ggml_status changed ggml_status from a bit-field type to simple codes ggml_status to string cast * ggml_status to string cast * GGML_CALL was removed Co-authored-by: slaren <slarengh@gmail.com> --------- Co-authored-by: slaren <slarengh@gmail.com> Co-authored-by: Georgi Gerganov <ggerganov@gmail.com> * sync : ggml ggml-ci * ggml : fix unknown status (#0) * flake : fix * llama : fix embeddings (ggerganov#5796) * llama : fix embeddings ggml-ci * llama : do not use KV cache for non-causal models ggml-ci * embeddings : fix llama_batch_init arg * llama : add pooling switch * llama : distinguish token vs sequence embeddings ggml-ci * llama : assert pooling tensor * llama : simplify causal mask condition ggml-ci * llama : assert input batch with pooling enabled * readme : update API changes list * nix: static build (ggerganov#5814) * fix speculative decoding build on windows (ggerganov#5874) * rebase and rm tailing space --------- Co-authored-by: LiangtaoJin <liang-tao.jin@intel.com> Co-authored-by: compilade <113953597+compilade@users.noreply.github.com> Co-authored-by: Jared Van Bortel <cebtenzzre@gmail.com> Co-authored-by: Xuan Son Nguyen <thichthat@gmail.com> Co-authored-by: Georgi Gerganov <ggerganov@gmail.com> Co-authored-by: Kawrakow <48489457+ikawrakow@users.noreply.github.com> Co-authored-by: Iwan Kawrakow <iwan.kawrakow@gmail.com> Co-authored-by: Jared Van Bortel <jared@nomic.ai> Co-authored-by: Michael Podvitskiy <podvitskiymichael@gmail.com> Co-authored-by: Pierrick Hymbert <pierrick.hymbert@gmail.com> Co-authored-by: github-actions[bot] <github-actions[bot]@users.noreply.github.com> Co-authored-by: Nindaleth <Nindaleth@users.noreply.github.com> Co-authored-by: Black_Fox <radekliska@gmail.com> Co-authored-by: Douglas Hanley <thesecretaryofwar@gmail.com> Co-authored-by: slaren <slarengh@gmail.com> Co-authored-by: DAN™ <dranger003@gmail.com> Co-authored-by: leejet <leejet714@gmail.com> Co-authored-by: Minsoo Cheong <54794500+mscheong01@users.noreply.github.com> Co-authored-by: Dane Madsen <dane_madsen@hotmail.com> Co-authored-by: hutli <6594598+hutli@users.noreply.github.com> Co-authored-by: Jeffrey Quesnelle <emozilla@nousresearch.com>

* llama : fix embeddings ggml-ci * llama : do not use KV cache for non-causal models ggml-ci * embeddings : fix llama_batch_init arg * llama : add pooling switch * llama : distinguish token vs sequence embeddings ggml-ci * llama : assert pooling tensor * llama : simplify causal mask condition ggml-ci * llama : assert input batch with pooling enabled * readme : update API changes list

@JohannesGaessler

* fix mul_mat fault in cpy_f32_f16 * rm unused function * add wait() for memcpy * restore ci/run.sh, rename struct defination, fix bug in ggml_sycl_op_mul_mat_sycl * fix format issue * llama : fix segfault from unknown model arch name (ggerganov#5820) * llama : fix segfault from unknown model arch name * llama : make all LLM maps const This also requires using `std::map::at` instead of its `operator[]` which does not exist for const maps. * llama : name LLM_ARCH_UNKNOWN to "(unknown)" This avoids errors from `std::map::at` when getting the general name of the model architecture. Using "(unknown)" instead of an empty string as per suggestion ggerganov#5820 (comment) * llama : remove redundant inner const for LLM_TENSOR_NAMES The extra const won't do anything here as const maps return const references to values. Co-authored-by: Jared Van Bortel <cebtenzzre@gmail.com> * llama : remove redundant nullptr check in llm_arch_from_string Since LLM_ARCH_NAMES is a const map, no spurious elements with a NULL name are inserted anymore, so this check is dead code. --------- Co-authored-by: Jared Van Bortel <cebtenzzre@gmail.com> * llama : refactor internal quantization functions (ggerganov#5830) * scripts : add pod-llama.sh * ggml : IQ3_S improvements (ggerganov#5829) * iq3_s: somewhat faster AVX2 dot product On Ryzen a 7950X TG-128 increases to 16 t/s from 15.5 t/s using 16 threads. For 8 threads it is 13.85 t/s vs 11.75 t/s. PP-512 increases to 28.5 t/s from 23.8 t/s. * iq3_s: somewhat faster ARM_NEON dot product Still dog slow - 10.7 t/s up from 9.9 t/s. * iq3_s: another small ARM_NEON improvement 10.7 -> 11.0 t/s. Using vmulq_s8 is faster than the xor - sub trick that works best on AVX2. * iq3_s: minor improvement on Metal 49.4 t/s -> 50.3 t/s * iq3_s: PPL improvement E.g., for a context of 4096 LLaMA-v2-7B goes to 5.1340 from 5.1653. * iq3_s: use new grid everywhere * Fix ARM_NEON --------- Co-authored-by: Iwan Kawrakow <iwan.kawrakow@gmail.com> * convert-hf : make model class definitions self-contained (ggerganov#5825) * convert : automatically fall back to HfVocab if tokenizer.model doesn't exist (ggerganov#5821) * ggml : fix IQ3_S AVX implementation (ggerganov#5834) ggml-ci * llama : add abort_callback to interrupt computation (ggerganov#5409) * using abort_callback from ggml to stop llama computation * format fix * a brief explaining comment --------- Co-authored-by: Georgi Gerganov <ggerganov@gmail.com> * server: tests: passkey challenge / self-extend with context shift demo (ggerganov#5832) * server: tests: add models endpoint scenario * server: /v1/models add some metadata * server: tests: add debug field in context before scenario * server: tests: download model from HF, add batch size * server: tests: add passkey test * server: tests: add group attention params * server: do not truncate prompt tokens if self-extend through group attention is enabled * server: logs: do not truncate log values * server: tests - passkey - first good working value of nga * server: tests: fix server timeout * server: tests: fix passkey, add doc, fix regex content matching, fix timeout * server: tests: fix regex content matching * server: tests: schedule slow tests on master * server: metrics: fix when no prompt processed * server: tests: self-extend add llama-2-7B and Mixtral-8x7B-v0.1 * server: tests: increase timeout for completion * server: tests: keep only the PHI-2 test * server: tests: passkey add a negative test * flake.lock: Update (ggerganov#5842) Flake lock file updates: • Updated input 'flake-parts': 'github:hercules-ci/flake-parts/b253292d9c0a5ead9bc98c4e9a26c6312e27d69f' (2024-02-01) → 'github:hercules-ci/flake-parts/f7b3c975cf067e56e7cda6cb098ebe3fb4d74ca2' (2024-03-01) • Updated input 'flake-parts/nixpkgs-lib': 'github:NixOS/nixpkgs/97b17f32362e475016f942bbdfda4a4a72a8a652?dir=lib' (2024-01-29) → 'github:NixOS/nixpkgs/1536926ef5621b09bba54035ae2bb6d806d72ac8?dir=lib' (2024-02-29) • Updated input 'nixpkgs': 'github:NixOS/nixpkgs/cbc4211f0afffe6dfd2478a62615dd5175a13f9a' (2024-02-23) → 'github:NixOS/nixpkgs/1536926ef5621b09bba54035ae2bb6d806d72ac8' (2024-02-29) Co-authored-by: github-actions[bot] <github-actions[bot]@users.noreply.github.com> * server : init http requests thread pool with --parallel if set (ggerganov#5836) * ci : schedule slow server tests only on Release or on demand (ggerganov#5839) * llama : fix llama_copy_state_data with fragmented KV cache (ggerganov#5840) The row size of the saved states was based on kv_self.head while it should be based on llama_kv_cache_cell_max. Existing session files should still work. * llama : fix llama_kv_cache_cell_max inability to return 1 I've also changed its return type to uint32_t, because this function is always used to set the value of uint32_t variables, and because the index already has this type. * llama : fix state size calculation Some bytes in the state were unaccounted for in llama_get_state_size. Since the logits reserve so much space, it did not cause problems. * gguf-dump : support i-quants (ggerganov#5841) Co-authored-by: Black_Fox <radekliska@gmail.com> * llama : allow for user specified embedding pooling type (ggerganov#5849) * allow for user specified pooling type * llama : use enum types over int --------- Co-authored-by: Georgi Gerganov <ggerganov@gmail.com> * readme : add API changes section * cuda : fix data race in soft max (ggerganov#5853) * main : support special tokens as reverse/anti prompt (ggerganov#5847) * Support special tokens as reverse/anti prompt. * Tokenize antiprompts only once. * main : minor --------- Co-authored-by: Georgi Gerganov <ggerganov@gmail.com> * common : use LLAMA_DEFAULT_SEED (ggerganov#5855) * add some new ops, fix some operators and add batch operations to certain operators. (ggml/747) * cuda: fix group_norm * cuda: add batch inference support for ggml_pad/ggml_upscale * add ggml_arrange * add ggml_timestep_embedding * update ggml_arange/ggml_timestep_embedding tests * cuda: fix im2col * add ggml_arange/ggml_timestep_embbeding support for metal backend * fix some bugs * fix some bugs * Update ggml.h Co-authored-by: Georgi Gerganov <ggerganov@gmail.com> * Update ggml-cuda.cu Co-authored-by: Georgi Gerganov <ggerganov@gmail.com> * Update ggml-metal.m Co-authored-by: Georgi Gerganov <ggerganov@gmail.com> * Update ggml-metal.m Co-authored-by: Georgi Gerganov <ggerganov@gmail.com> * Update ggml-metal.metal Co-authored-by: Georgi Gerganov <ggerganov@gmail.com> * modify according to the review comments * ggml : fix compile warnings + code style * ggml : normalize compute_forward calls + fix seg fault in debug * minor --------- Co-authored-by: Georgi Gerganov <ggerganov@gmail.com> Co-authored-by: slaren <slarengh@gmail.com> * sync : ggml * add alias for chat template (ggerganov#5858) * speculative : implement stochastic speculative sampling (ggerganov#5625) * (WIP) Implement stochastic speculative decoding * sample from residual distribution on draft accept failure * fix ggerganov#5657: force greedy sampling with probs when temp is 0 * remove p_accept parameter * fix style * remove unused variables * add srand() in speculative.cpp * replace use of rand() with mt19937 sampling * fixes based on review (@JohannesGaessler) * fix r random generation * randomly select next sequence to verify + fix bug in memory freeing * fix bug in active_seqs sync * fix uniform int distribution initialization * remove warnings from comparison between int and size_t * check grammar in `llama_sample_probability_distribution_impl` * remove malloc code by utilizing vectors * add PR link to README * cmake : handle cases where git index is not found in .git (ggerganov#5844) * Update CMakeLists.txt * Update CMakeLists.txt * ggml : introduce ggml_status (ggml/750) * using enum as an exit code instead of macros * update return type from enum to unsigned int * indentation fix * compound update ggml_compute_exit_code -> ggml_status changed ggml_status from a bit-field type to simple codes ggml_status to string cast * ggml_status to string cast * GGML_CALL was removed Co-authored-by: slaren <slarengh@gmail.com> --------- Co-authored-by: slaren <slarengh@gmail.com> Co-authored-by: Georgi Gerganov <ggerganov@gmail.com> * sync : ggml ggml-ci * ggml : fix unknown status (#0) * flake : fix * llama : fix embeddings (ggerganov#5796) * llama : fix embeddings ggml-ci * llama : do not use KV cache for non-causal models ggml-ci * embeddings : fix llama_batch_init arg * llama : add pooling switch * llama : distinguish token vs sequence embeddings ggml-ci * llama : assert pooling tensor * llama : simplify causal mask condition ggml-ci * llama : assert input batch with pooling enabled * readme : update API changes list * nix: static build (ggerganov#5814) * fix speculative decoding build on windows (ggerganov#5874) * rebase and rm tailing space --------- Co-authored-by: LiangtaoJin <liang-tao.jin@intel.com> Co-authored-by: compilade <113953597+compilade@users.noreply.github.com> Co-authored-by: Jared Van Bortel <cebtenzzre@gmail.com> Co-authored-by: Xuan Son Nguyen <thichthat@gmail.com> Co-authored-by: Georgi Gerganov <ggerganov@gmail.com> Co-authored-by: Kawrakow <48489457+ikawrakow@users.noreply.github.com> Co-authored-by: Iwan Kawrakow <iwan.kawrakow@gmail.com> Co-authored-by: Jared Van Bortel <jared@nomic.ai> Co-authored-by: Michael Podvitskiy <podvitskiymichael@gmail.com> Co-authored-by: Pierrick Hymbert <pierrick.hymbert@gmail.com> Co-authored-by: github-actions[bot] <github-actions[bot]@users.noreply.github.com> Co-authored-by: Nindaleth <Nindaleth@users.noreply.github.com> Co-authored-by: Black_Fox <radekliska@gmail.com> Co-authored-by: Douglas Hanley <thesecretaryofwar@gmail.com> Co-authored-by: slaren <slarengh@gmail.com> Co-authored-by: DAN™ <dranger003@gmail.com> Co-authored-by: leejet <leejet714@gmail.com> Co-authored-by: Minsoo Cheong <54794500+mscheong01@users.noreply.github.com> Co-authored-by: Dane Madsen <dane_madsen@hotmail.com> Co-authored-by: hutli <6594598+hutli@users.noreply.github.com> Co-authored-by: Jeffrey Quesnelle <emozilla@nousresearch.com>

* Updated binaries, using [this build](https://github.com/SciSharp/LLamaSharp/actions/runs/8654672719/job/23733195669) for llama.cpp commit `f7001ccc5aa359fcf41bba19d1c99c3d25c9bcc7`. - Added all new functions. - Moved some functions (e.g. `SafeLlamaModelHandle` specific functions) into `SafeLlamaModelHandle.cs` - Exposed tokens on `SafeLlamaModelHandle` and `LLamaWeights` through a `Tokens` property. As new special tokens are added in the future they can be added here. - Changed all token properties to return nullable tokens, to handle some models not having some tokens. - Fixed `DefaultSamplingPipeline` to handle no newline token in some models. * Moved native methods to more specific locations. - Context specific things have been moved into `SafeLLamaContextHandle.cs` and made private - they're exposed through C# properties and methods already. - Checking that GPU layer count is zero if GPU offload is not supported. - Moved methods for creating default structs (`llama_model_quantize_default_params` and `llama_context_default_params`) into relevant structs. * Removed exception if `GpuLayerCount > 0` when GPU is not supported. * - Added low level wrapper methods for new per-sequence state load/save in `SafeLLamaContextHandle` - Added high level wrapper methods (save/load with `State` object or memory mapped file) in `LLamaContext` - Moved native methods for per-sequence state load/save into `SafeLLamaContextHandle` * Added update and defrag methods for KV cache in `SafeLLamaContextHandle` * Updated submodule to `f7001ccc5aa359fcf41bba19d1c99c3d25c9bcc7` * Passing the sequence ID when saving a single sequence state

cebtenzzre reviewed Feb 29, 2024

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ggerganov marked this pull request as draft February 29, 2024 19:44

ngxson mentioned this pull request Feb 29, 2024

Inconsistent Bert Embedding output from embedding.cpp vs llama.cpp server #5801

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iamlemec reviewed Feb 29, 2024

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regstuff mentioned this pull request Mar 2, 2024

Works great on command line, but unable to use via python iamlemec/bert.cpp#15

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iamlemec mentioned this pull request Mar 3, 2024

Allow for user specified embedding pooling type #5849

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llama : fix embeddings

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ggerganov force-pushed the gg/fix-embeddings branch from 008f3fc to d034784 Compare March 4, 2024 09:44

ggerganov commented Mar 4, 2024

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ggerganov added 3 commits March 4, 2024 13:34

llama : do not use KV cache for non-causal models

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embeddings : fix llama_batch_init arg

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llama : add pooling switch

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ggerganov marked this pull request as ready for review March 4, 2024 12:39

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ggerganov added 2 commits March 4, 2024 19:14

llama : distinguish token vs sequence embeddings

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llama : assert pooling tensor

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ggerganov added 3 commits March 4, 2024 19:40

llama : simplify causal mask condition

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ggml-ci

llama : assert input batch with pooling enabled

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readme : update API changes list

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ggerganov merged commit 29ae62d into master Mar 4, 2024
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ggerganov deleted the gg/fix-embeddings branch March 4, 2024 20:31

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Hirtol mentioned this pull request Mar 5, 2024

Add Embedding Related Functionality utilityai/llama-cpp-rs#133

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ggerganov mentioned this pull request Mar 5, 2024

llama : compute BERT graph with F16 K, V #5891

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iamlemec mentioned this pull request Mar 8, 2024

Switch embed to llama_get_embeddings_seq abetlen/llama-cpp-python#1263

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cebtenzzre mentioned this pull request Mar 12, 2024

Nomic Embed integration via llama.cpp BERT implementation nomic-ai/gpt4all#2086

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llama : fix embeddings #5796

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