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Awesome GitHub RepositoriesFine-Tuning Tutorials
Guides and code examples for adapting pre-trained machine learning models to specific tasks or datasets.
Distinguishing note: No existing candidates provided; this captures the educational aspect of model adaptation.
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Awesome Fine-Tuning Tutorials GitHub Repositories
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- datawhalechina/self-llm
datawhalechina/self-llm
28,285View on GitHubThis project is an open-source educational resource providing structured, step-by-step guides for fine-tuning large language models. It focuses on adapting pre-trained transformer-based causal models to custom datasets, enabling users to transfer specific writing styles or domain knowledge into generative AI models. The repository distinguishes itself by emphasizing parameter-efficient training techniques, specifically low-rank adaptation. By providing practical implementations for updating only a small subset of model weights, it allows for the customization of massive neural networks on con
训练好了之后可以使用如下方式加载lora权重进行推理： ```python from transformers import AutoModelForCausalLM, AutoTokenizer import torch from peft import PeftModel modepath = '/root/autodl-tmp/LLM-Research/Meta-Llama-3-8B-Instruct' lorapath
Jupyter Notebookchatglmchatglm3gemma-2b-it
