Instructions to use SamChen888/Mistral-EN-Part-2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use SamChen888/Mistral-EN-Part-2 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-2") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Unsloth Desktop
Download training_args.bin from SamChen888/Mistral-EN-Part-2: direct link, hf CLI and curl.
- Browser
- Download file 5.69 kB
-
https://huggingface.co/SamChen888/Mistral-EN-Part-2/resolve/main/training_args.bin
- Command line
-
hf download hf://SamChen888/Mistral-EN-Part-2/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/SamChen888/Mistral-EN-Part-2/resolve/main/training_args.bin
5.69 kB
- Xet hash:
- d914be9b9f709638a9ca069e477ce172cfe00f582041a75fb4f4f48cd9419093
- Size of remote file:
- 5.69 kB
- SHA256:
- 7c0f50151d95e9d064572887223a75b34b8d863adcbd94f03a50070eddf5f434
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