Instructions to use nhungphammmmm/9f9a22c6-4fe3-4f6b-8627-3d9503bf0ecc with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use nhungphammmmm/9f9a22c6-4fe3-4f6b-8627-3d9503bf0ecc with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("HuggingFaceH4/zephyr-7b-beta") model = PeftModel.from_pretrained(base_model, "nhungphammmmm/9f9a22c6-4fe3-4f6b-8627-3d9503bf0ecc") - Notebooks
- Google Colab
- Kaggle
Download adapter_model.safetensors from nhungphammmmm/9f9a22c6-4fe3-4f6b-8627-3d9503bf0ecc: direct link, hf CLI and curl.
- Browser
- Download file 83.9 MB
-
https://huggingface.co/nhungphammmmm/9f9a22c6-4fe3-4f6b-8627-3d9503bf0ecc/resolve/main/adapter_model.safetensors
- Command line
-
hf download hf://nhungphammmmm/9f9a22c6-4fe3-4f6b-8627-3d9503bf0ecc/adapter_model.safetensors
-
curl -L -o adapter_model.safetensors https://huggingface.co/nhungphammmmm/9f9a22c6-4fe3-4f6b-8627-3d9503bf0ecc/resolve/main/adapter_model.safetensors
83.9 MB
- Xet hash:
- 0090eab2338487abc59a436b13a036848ea133a01b4bce8f49b635e36a044fb1
- Size of remote file:
- 83.9 MB
- SHA256:
- 1df728aa16e449d05f8e29f5a100f53deee3edb3c54b7b5f2f6f430efac44cd3
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