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 Mistral_torch_model.bin from codegood/MistralLite_SC: direct link, hf CLI and curl.
- Browser
- Download file 5.02 GB
-
https://huggingface.co/codegood/MistralLite_SC/resolve/main/Mistral_torch_model.bin
- Command line
-
hf download hf://codegood/MistralLite_SC/Mistral_torch_model.bin
-
curl -L -o Mistral_torch_model.bin https://huggingface.co/codegood/MistralLite_SC/resolve/main/Mistral_torch_model.bin
5.02 GB
- Xet hash:
- 9be4d6a31b9250f42320eca217969b51a66959dbca04ead1e250737fea6c0c63
- Size of remote file:
- 5.02 GB
- SHA256:
- 1407bee66ed6460f3f79b0cbd305abf5515e21b9d9eacb0af04b6ae494a8d66a
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