Instructions to use bachbouch/w-3-qlora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use bachbouch/w-3-qlora with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("mistralai/Mistral-7B-Instruct-v0.2") model = PeftModel.from_pretrained(base_model, "bachbouch/w-3-qlora") - Notebooks
- Google Colab
- Kaggle
Download optimizer.pt from bachbouch/w-3-qlora: direct link, hf CLI and curl.
- Browser
- Download file 43.1 MB
-
https://huggingface.co/bachbouch/w-3-qlora/resolve/main/optimizer.pt
- Command line
-
hf download hf://bachbouch/w-3-qlora/optimizer.pt
-
curl -L -o optimizer.pt https://huggingface.co/bachbouch/w-3-qlora/resolve/main/optimizer.pt
43.1 MB
- Xet hash:
- 64a91da94706d37f4341f6ed62f1dea11ad8e2c92a870cfe05cf4c5f8619bad8
- Size of remote file:
- 43.1 MB
- SHA256:
- 8c9956de091997ade300b414e60796b0834186e53c408c33e18b4e943723ccb9
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