tiny fix
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@ -46,7 +46,7 @@ Choose your path:
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- **Various models**: LLaMA, Mistral, Mixtral-MoE, Qwen, Yi, Gemma, Baichuan, ChatGLM, Phi, etc.
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- **Integrated methods**: (Continuous) pre-training, supervised fine-tuning, reward modeling, PPO, DPO and ORPO.
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- **Scalable resources**: 32-bit full-tuning, 16-bit freeze-tuning, 16-bit LoRA and 2/4/8-bit QLoRA via AQLM/AWQ/GPTQ/LLM.int8.
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- **Advanced algorithms**: GaLore, BAdam, DoRA, LongLoRA, LLaMA Pro, LoRA+, LoftQ and Agent tuning.
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- **Advanced algorithms**: GaLore, DoRA, LongLoRA, LLaMA Pro, LoRA+, LoftQ and Agent tuning.
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- **Practical tricks**: FlashAttention-2, Unsloth, RoPE scaling, NEFTune and rsLoRA.
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- **Experiment monitors**: LlamaBoard, TensorBoard, Wandb, MLflow, etc.
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- **Faster inference**: OpenAI-style API, Gradio UI and CLI with vLLM worker.
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@ -309,7 +309,7 @@ cd LLaMA-Factory
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pip install -e .[metrics]
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```
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Extra dependencies available: deepspeed, metrics, unsloth, galore, vllm, bitsandbytes, gptq, awq, aqlm, qwen, modelscope, quality
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Extra dependencies available: deepspeed, metrics, unsloth, galore, badam, vllm, bitsandbytes, gptq, awq, aqlm, qwen, modelscope, quality
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<details><summary>For Windows users</summary>
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@ -309,7 +309,7 @@ cd LLaMA-Factory
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pip install -e .[metrics]
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```
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可选的额外依赖项:deepspeed、metrics、unsloth、galore、vllm、bitsandbytes、gptq、awq、aqlm、qwen、modelscope、quality
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可选的额外依赖项:deepspeed、metrics、unsloth、galore、badam、vllm、bitsandbytes、gptq、awq、aqlm、qwen、modelscope、quality
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<details><summary>Windows 用户指南</summary>
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@ -66,7 +66,6 @@ def check_dependencies() -> None:
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require_version("accelerate>=0.27.2", "To fix: pip install accelerate>=0.27.2")
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require_version("peft>=0.10.0", "To fix: pip install peft>=0.10.0")
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require_version("trl>=0.8.1", "To fix: pip install trl>=0.8.1")
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require_version("gradio>=4.0.0", "To fix: pip install gradio>=4.0.0")
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def count_parameters(model: torch.nn.Module) -> Tuple[int, int]:
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