Instructions to use CharlesLi/mistral_per_class_reflect_lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use CharlesLi/mistral_per_class_reflect_lora with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("mistralai/Mistral-7B-Instruct-v0.1") model = PeftModel.from_pretrained(base_model, "CharlesLi/mistral_per_class_reflect_lora") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from CharlesLi/mistral_per_class_reflect_lora: direct link, hf CLI and curl.
- Browser
- Download file 1.8 MB
-
https://huggingface.co/CharlesLi/mistral_per_class_reflect_lora/resolve/main/tokenizer.json
- Command line
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hf download hf://CharlesLi/mistral_per_class_reflect_lora/tokenizer.json
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curl -L -o tokenizer.json https://huggingface.co/CharlesLi/mistral_per_class_reflect_lora/resolve/main/tokenizer.json
1.8 MB
File too large to display, you can check the raw version instead.