Instructions to use Cem13/3mixi with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use Cem13/3mixi with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("mistralai/Mixtral-8x7B-Instruct-v0.1") model = PeftModel.from_pretrained(base_model, "Cem13/3mixi") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from Cem13/3mixi: direct link, hf CLI and curl.
- Browser
- Download file 4.98 kB
-
https://huggingface.co/Cem13/3mixi/resolve/main/training_args.bin
- Command line
-
hf download hf://Cem13/3mixi/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/Cem13/3mixi/resolve/main/training_args.bin
4.98 kB
- Xet hash:
- 2bb31b6d2c6c50246780c7c21c3080c1686db04991a76ef72742ca8aa1a25d9c
- Size of remote file:
- 4.98 kB
- SHA256:
- 4381f0a9cf1919f08f89ac620688894c20277a15e0528e9828592508d06f1218
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