Instructions to use codegood/MistralLite_SC with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use codegood/MistralLite_SC with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("amazon/MistralLite") model = PeftModel.from_pretrained(base_model, "codegood/MistralLite_SC") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from codegood/MistralLite_SC: direct link, hf CLI and curl.
- Browser
- Download file 4.09 kB
-
https://huggingface.co/codegood/MistralLite_SC/resolve/main/training_args.bin
- Command line
-
hf download hf://codegood/MistralLite_SC/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/codegood/MistralLite_SC/resolve/main/training_args.bin
4.09 kB
- Xet hash:
- bbb53fefe5db5abdfc144cfbfc200c60b8aee58d7f5dba9dea5642a0961cc651
- Size of remote file:
- 4.09 kB
- SHA256:
- 6a2cfeda732283b3486b84f59dc3ab9d51409fa065384956a95018c245f7aed8
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