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jayzeng
/
llm-fun

PEFT
TensorBoard
Safetensors
qwen2_moe
Generated from Trainer
4-bit precision
bitsandbytes
Model card Files Files and versions
xet
Metrics Training metrics Community

Instructions to use jayzeng/llm-fun with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • PEFT

    How to use jayzeng/llm-fun with PEFT:

    from peft import PeftModel
    from transformers import AutoModelForCausalLM
    
    base_model = AutoModelForCausalLM.from_pretrained("Qwen/Qwen1.5-MoE-A2.7B")
    model = PeftModel.from_pretrained(base_model, "jayzeng/llm-fun")
  • Notebooks
  • Google Colab
  • Kaggle
llm-fun
14.4 GB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 2 commits
jayzeng's picture
jayzeng
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a3b07fb verified over 2 years ago
  • checkpoint-1425
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  • checkpoint-1900
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  • checkpoint-475
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  • checkpoint-950
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  • runs
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  • .gitattributes
    1.52 kB
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  • README.md
    3.55 kB
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  • adapter_config.json
    762 Bytes
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  • adapter_model.bin

    Detected Pickle imports (3)

    • "torch._utils._rebuild_tensor_v2",
    • "torch.FloatStorage",
    • "collections.OrderedDict"

    What is a pickle import?

    2.05 GB
    xet
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  • added_tokens.json
    80 Bytes
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  • config.json
    1.42 kB
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  • merges.txt
    1.67 MB
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  • special_tokens_map.json
    370 Bytes
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  • tokenizer.json
    7.03 MB
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  • tokenizer_config.json
    1.3 kB
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  • vocab.json
    2.78 MB
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