Instructions to use shibajustfor/52d764a2-36a2-46a7-8625-8e78f8248449 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use shibajustfor/52d764a2-36a2-46a7-8625-8e78f8248449 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/SmolLM-135M-Instruct") model = PeftModel.from_pretrained(base_model, "shibajustfor/52d764a2-36a2-46a7-8625-8e78f8248449") - Notebooks
- Google Colab
- Kaggle
Download adapter_model.bin from shibajustfor/52d764a2-36a2-46a7-8625-8e78f8248449: direct link, hf CLI and curl.
- Browser
- Download file 9.92 MB
-
https://huggingface.co/shibajustfor/52d764a2-36a2-46a7-8625-8e78f8248449/resolve/main/adapter_model.bin
- Command line
-
hf download hf://shibajustfor/52d764a2-36a2-46a7-8625-8e78f8248449/adapter_model.bin
-
curl -L -o adapter_model.bin https://huggingface.co/shibajustfor/52d764a2-36a2-46a7-8625-8e78f8248449/resolve/main/adapter_model.bin
9.92 MB
- Xet hash:
- cb4836fa3bc824cc658f48bdeb7c68854c876590d6bf60b76ae42d5f47846414
- Size of remote file:
- 9.92 MB
- SHA256:
- 8f5dd87580889b33601449baea2b01f88fe93a451f389710ad095f93bf163aa4
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