Instructions to use H83/mistral_instruct_generation with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use H83/mistral_instruct_generation with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("mistralai/Mixtral-8x7B-v0.1") model = PeftModel.from_pretrained(base_model, "H83/mistral_instruct_generation") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from H83/mistral_instruct_generation: direct link, hf CLI and curl.
- Browser
- Download file 4.98 kB
-
https://huggingface.co/H83/mistral_instruct_generation/resolve/main/training_args.bin
- Command line
-
hf download hf://H83/mistral_instruct_generation/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/H83/mistral_instruct_generation/resolve/main/training_args.bin
4.98 kB
- Xet hash:
- 40e75b9714cf833a2371ace2d61c5114ff3550991b859d65104141dcc8e2894d
- Size of remote file:
- 4.98 kB
- SHA256:
- d087749d3472fa841e308d385e83ceede86f83100503dbf4db781c632bfe2e9b
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.