Axolotl

Headlines · 2

1. 5d
   A practical guide to SFT and LoRA with Qwen3-0.6B-Base

   The Juejin AI tutorial explains how supervised fine-tuning adapts a base model to follow instructions, covering loss masking, Alpaca and ShareGPT data formats, and approaches such as Self-Instruct and model distillation. It demonstrates LoRA-based fine-tuning of Qwen3-0.6B-Base with TRL and PEFT, including code, configuration choices, and guidance on matching training and inference chat templates. The author reports that a 1,000-sample run on a 16 GB M2 Mac took about 44 minutes and changed the model from repeating questions into answering them completely.

   掘金 · 人工智能 · 🔥 0
2. Oct 11
   Hugging Face Transformers tops GitHub Trending

   Hugging Face's Transformers library appeared on GitHub Trending's daily list. The project positions itself as the model-definition framework for state-of-the-art text, vision, audio, video and multimodal models, for both inference and training, and its documentation says there are over 1M Transformers model checkpoints on the Hugging Face Hub. It says the library interoperates with training frameworks such as Axolotl, Unsloth, DeepSpeed, FSDP and PyTorch-Lightning, and with inference engines and modeling libraries including vLLM, SGLang, TGI, llama.cpp and mlx, and requires Python 3.10+ and PyTorch 2.6+.

   GitHub Trending（每日） · 🔥 0

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