Instructions to use kk-aivio/b90bff2f-226e-48c0-a878-ef39a7c280a0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use kk-aivio/b90bff2f-226e-48c0-a878-ef39a7c280a0 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("Intel/neural-chat-7b-v3-3") model = PeftModel.from_pretrained(base_model, "kk-aivio/b90bff2f-226e-48c0-a878-ef39a7c280a0") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from kk-aivio/b90bff2f-226e-48c0-a878-ef39a7c280a0: direct link, hf CLI and curl.
- Browser
- Download file 6.78 kB
-
https://huggingface.co/kk-aivio/b90bff2f-226e-48c0-a878-ef39a7c280a0/resolve/main/training_args.bin
- Command line
-
hf download hf://kk-aivio/b90bff2f-226e-48c0-a878-ef39a7c280a0/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/kk-aivio/b90bff2f-226e-48c0-a878-ef39a7c280a0/resolve/main/training_args.bin
6.78 kB
- Xet hash:
- 10b642a969236a43c42cc5bf4f482d05cd30294c633f77e485f19fb41f129958
- Size of remote file:
- 6.78 kB
- SHA256:
- 6e4b05309363d9d06e53a2506b917d72f07fe758005f25f3c1baed00218cec93
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