Instructions to use seop-du/mistral_question_decomposition with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use seop-du/mistral_question_decomposition with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("mistralai/Mistral-7B-Instruct-v0.1") model = PeftModel.from_pretrained(base_model, "seop-du/mistral_question_decomposition") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.model from seop-du/mistral_question_decomposition: direct link, hf CLI and curl.
- Browser
- Download file 493 kB
-
https://huggingface.co/seop-du/mistral_question_decomposition/resolve/main/tokenizer.model
- Command line
-
hf download hf://seop-du/mistral_question_decomposition/tokenizer.model
-
curl -L -o tokenizer.model https://huggingface.co/seop-du/mistral_question_decomposition/resolve/main/tokenizer.model
493 kB
- Xet hash:
- 1e090c2d2774ea7875da72d682c12600bd69085e9c28674b917a49fe82ccffe2
- Size of remote file:
- 493 kB
- SHA256:
- dadfd56d766715c61d2ef780a525ab43b8e6da4de6865bda3d95fdef5e134055
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.