Instructions to use SamChen888/Mistral-EN-Part-1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use SamChen888/Mistral-EN-Part-1 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/mistral-7b-instruct-v0.3-bnb-4bit") model = PeftModel.from_pretrained(base_model, "SamChen888/Mistral-EN-Part-1") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Unsloth Desktop
Download training_args.bin from SamChen888/Mistral-EN-Part-1: direct link, hf CLI and curl.
- Browser
- Download file 5.69 kB
-
https://huggingface.co/SamChen888/Mistral-EN-Part-1/resolve/main/training_args.bin
- Command line
-
hf download hf://SamChen888/Mistral-EN-Part-1/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/SamChen888/Mistral-EN-Part-1/resolve/main/training_args.bin
5.69 kB
- Xet hash:
- 0e536b59d1a4975cf217615279839ed8c7bdedf72ac8d47d3bbc89037ba2d032
- Size of remote file:
- 5.69 kB
- SHA256:
- 0b3cb86ceab1094d776b1ec437de8d7cd5b248aebd6997bd76c45f08cd0a4571
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