Instructions to use AKM15/Mixtral_Alpace_v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use AKM15/Mixtral_Alpace_v2 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, "AKM15/Mixtral_Alpace_v2") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from AKM15/Mixtral_Alpace_v2: direct link, hf CLI and curl.
- Browser
- Download file 4.73 kB
-
https://huggingface.co/AKM15/Mixtral_Alpace_v2/resolve/main/training_args.bin
- Command line
-
hf download hf://AKM15/Mixtral_Alpace_v2/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/AKM15/Mixtral_Alpace_v2/resolve/main/training_args.bin
4.73 kB
- Xet hash:
- fbdf9331afba39ecc1120edc07333ceb479111b9f3ac4f23666bf0debe75f56e
- Size of remote file:
- 4.73 kB
- SHA256:
- 2156883feb60a099eb1b596b379a4fa68c6b66605d6bc92cece2ee5e6a7f245b
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