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minor fixes 20231211 #943

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minor fixes 20231211 #943

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2de1bfa
misc fixes
winglian Dec 12, 2023
2f600e2
nano editor in base docker
winglian Dec 12, 2023
8c78197
move nano install to axolotl image
winglian Dec 12, 2023
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2 changes: 1 addition & 1 deletion docker/Dockerfile
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Expand Up @@ -10,7 +10,7 @@ ARG PYTORCH_VERSION="2.0.1"
ENV PYTORCH_VERSION=$PYTORCH_VERSION

RUN apt-get update && \
apt-get install -y vim curl
apt-get install -y vim curl nano

WORKDIR /workspace

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1 change: 1 addition & 0 deletions docker/Dockerfile-runpod
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Expand Up @@ -5,6 +5,7 @@ ENV HF_DATASETS_CACHE="/workspace/data/huggingface-cache/datasets"
ENV HUGGINGFACE_HUB_CACHE="/workspace/data/huggingface-cache/hub"
ENV TRANSFORMERS_CACHE="/workspace/data/huggingface-cache/hub"
ENV HF_HOME="/workspace/data/huggingface-cache/hub"
ENV HF_HUB_ENABLE_HF_TRANSFER=1

COPY scripts/runpod-entrypoint.sh /root/runpod-entrypoint.sh

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4 changes: 4 additions & 0 deletions src/axolotl/cli/merge_lora.py
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Expand Up @@ -20,6 +20,10 @@ def do_cli(config: Path = Path("examples/"), **kwargs):
parsed_cli_args.merge_lora = True
parsed_cfg = load_cfg(config, merge_lora=True, **kwargs)

parsed_cfg.load_in_4bit = False
parsed_cfg.load_in_8bit = False
parsed_cfg.flash_attention = False

do_merge_lora(cfg=parsed_cfg, cli_args=parsed_cli_args)


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3 changes: 2 additions & 1 deletion src/axolotl/utils/models.py
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Expand Up @@ -191,6 +191,7 @@ def load_model(

# TODO refactor as a kwarg
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there's this todo here.

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I'm not even sure what this TODO is for atm

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maybe it's for the .from_pretrained call where these are kwargs for that? should we add this to model_kwargs and remove those from all the from_pretrained calls?

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This is just above

   load_in_8bit = cfg.load_in_8bit
     load_in_4bit = cfg.load_in_4bit

load_in_8bit = cfg.load_in_8bit
load_in_4bit = cfg.load_in_4bit

if hasattr(model_config, "model_type") and model_config.model_type == "btlm":
if cfg.flash_attention:
Expand Down Expand Up @@ -535,7 +536,7 @@ def load_model(

model, lora_config = load_adapter(model, cfg, cfg.adapter)

if cfg.ddp and not load_in_8bit:
if cfg.ddp and not load_in_8bit and not load_in_4bit:
model.to(f"cuda:{cfg.local_rank}")
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what's the side effect of this change? Does it mean, the models will all live on gpu0 for 4 bit now?

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there's an edge case that I had to have this set when doing DPO qlora for Mixstral. maybe it was a deepspeed thing and I should change this?


if torch.cuda.device_count() > 1 and int(os.getenv("WORLD_SIZE", "1")) == 1:
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