Instructions to use havinash-ai/61a5ea63-24c3-44a9-be77-a2f139317391 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use havinash-ai/61a5ea63-24c3-44a9-be77-a2f139317391 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, "havinash-ai/61a5ea63-24c3-44a9-be77-a2f139317391") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from havinash-ai/61a5ea63-24c3-44a9-be77-a2f139317391: direct link, hf CLI and curl.
- Browser
- Download file 6.78 kB
-
https://huggingface.co/havinash-ai/61a5ea63-24c3-44a9-be77-a2f139317391/resolve/main/training_args.bin
- Command line
-
hf download hf://havinash-ai/61a5ea63-24c3-44a9-be77-a2f139317391/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/havinash-ai/61a5ea63-24c3-44a9-be77-a2f139317391/resolve/main/training_args.bin
6.78 kB
- Xet hash:
- 03e2285e02e843457488ab2859d294a2593271f2a7a00f245d3033ffd26d06db
- Size of remote file:
- 6.78 kB
- SHA256:
- 0875dd4cd951509b55366458a44c2d7a82c99c843eea114596d3028f1b4486dd
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