Closed
Description
Name and Version
root@f7545b6b4f65:/app# ./llama-cli --version
load_backend: loaded CPU backend from ./libggml-cpu-alderlake.so
version: 4460 (ba8a1f9)
built with cc (Ubuntu 11.4.0-1ubuntu1~22.04) 11.4.0 for x86_64-linux-gnu
Operating systems
Linux, Other? (Please let us know in description)
Which llama.cpp modules do you know to be affected?
llama-quantize
Command line
❯ docker run --rm -it \
-v ./models:/models \
ghcr.io/ggerganov/llama.cpp:full \
--quantize /models/BAAI/bge-small-en-v1.5/bge-small-en-v1.5-f32.gguf /models/BAAI/bge-small-en-v1.5/bge-small-en-v1.5-Q4_K_M.gguf Q4_K_MProblem description & steps to reproduce
just try to quantize a model and you'll get the segfault
❯ docker run --rm -it \
-v ./models:/models \
ghcr.io/ggerganov/llama.cpp:full \
--quantize /models/BAAI/bge-small-en-v1.5/bge-small-en-v1.5-f32.gguf /models/BAAI/bge-small-en-v1.5/bge-small-en-v1.5-Q4_K_M.gguf Q4_K_M
main: build = 4460 (ba8a1f9c)
main: built with cc (Ubuntu 11.4.0-1ubuntu1~22.04) 11.4.0 for x86_64-linux-gnu
main: quantizing '/models/BAAI/bge-small-en-v1.5/bge-small-en-v1.5-f32.gguf' to '/models/BAAI/bge-small-en-v1.5/bge-small-en-v1.5-Q4_K_M.gguf' as Q4_K_M
llama_model_loader: loaded meta data with 30 key-value pairs and 197 tensors from /models/BAAI/bge-small-en-v1.5/bge-small-en-v1.5-f32.gguf (version GGUF V3 (latest))
llama_model_loader: Dumping metadata keys/values. Note: KV overrides do not apply in this output.
llama_model_loader: - kv 0: general.architecture str = bert
llama_model_loader: - kv 1: general.type str = model
llama_model_loader: - kv 2: general.name str = Bge Small En v1.5
llama_model_loader: - kv 3: general.version str = v1.5
llama_model_loader: - kv 4: general.finetune str = en
llama_model_loader: - kv 5: general.basename str = bge
llama_model_loader: - kv 6: general.size_label str = small
llama_model_loader: - kv 7: general.license str = mit
llama_model_loader: - kv 8: general.tags arr[str,5] = ["sentence-transformers", "feature-ex...
llama_model_loader: - kv 9: general.languages arr[str,1] = ["en"]
llama_model_loader: - kv 10: bert.block_count u32 = 12
llama_model_loader: - kv 11: bert.context_length u32 = 512
llama_model_loader: - kv 12: bert.embedding_length u32 = 384
llama_model_loader: - kv 13: bert.feed_forward_length u32 = 1536
llama_model_loader: - kv 14: bert.attention.head_count u32 = 12
llama_model_loader: - kv 15: bert.attention.layer_norm_epsilon f32 = 0.000000
llama_model_loader: - kv 16: general.file_type u32 = 0
llama_model_loader: - kv 17: bert.attention.causal bool = false
llama_model_loader: - kv 18: bert.pooling_type u32 = 2
llama_model_loader: - kv 19: tokenizer.ggml.token_type_count u32 = 2
llama_model_loader: - kv 20: tokenizer.ggml.model str = bert
llama_model_loader: - kv 21: tokenizer.ggml.pre str = jina-v2-en
llama_model_loader: - kv 22: tokenizer.ggml.tokens arr[str,30522] = ["[PAD]", "[unused0]", "[unused1]", "...
llama_model_loader: - kv 23: tokenizer.ggml.token_type arr[i32,30522] = [3, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, ...
llama_model_loader: - kv 24: tokenizer.ggml.unknown_token_id u32 = 100
llama_model_loader: - kv 25: tokenizer.ggml.seperator_token_id u32 = 102
llama_model_loader: - kv 26: tokenizer.ggml.padding_token_id u32 = 0
llama_model_loader: - kv 27: tokenizer.ggml.cls_token_id u32 = 101
llama_model_loader: - kv 28: tokenizer.ggml.mask_token_id u32 = 103
llama_model_loader: - kv 29: general.quantization_version u32 = 2
llama_model_loader: - type f32: 197 tensors
Segmentation fault (core dumped)First Bad Commit
No response
Relevant log output
No response