Instructions to use shibajustfor/81a42206-7028-47a9-ad86-76875d8a859b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use shibajustfor/81a42206-7028-47a9-ad86-76875d8a859b 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, "shibajustfor/81a42206-7028-47a9-ad86-76875d8a859b") - Notebooks
- Google Colab
- Kaggle
Download adapter_model.bin from shibajustfor/81a42206-7028-47a9-ad86-76875d8a859b: direct link, hf CLI and curl.
- Browser
- Download file 336 MB
-
https://huggingface.co/shibajustfor/81a42206-7028-47a9-ad86-76875d8a859b/resolve/main/adapter_model.bin
- Command line
-
hf download hf://shibajustfor/81a42206-7028-47a9-ad86-76875d8a859b/adapter_model.bin
-
curl -L -o adapter_model.bin https://huggingface.co/shibajustfor/81a42206-7028-47a9-ad86-76875d8a859b/resolve/main/adapter_model.bin
336 MB
- Xet hash:
- ff53d7bcfbebedd7f5469854f4707ea0fbdc92b0f18ec9408e10be1118a29521
- Size of remote file:
- 336 MB
- SHA256:
- 779e1c64a1fb7bf7f20d196838cb7ce9f5f40b7d722db73642d04ce23e14c8a2
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