Instructions to use gavrilstep/d7d8672e-e993-46ee-a2dd-a1a4a4786574 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use gavrilstep/d7d8672e-e993-46ee-a2dd-a1a4a4786574 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/Qwen2-0.5B-Instruct") model = PeftModel.from_pretrained(base_model, "gavrilstep/d7d8672e-e993-46ee-a2dd-a1a4a4786574") - Notebooks
- Google Colab
- Kaggle
Download adapter_model.safetensors from gavrilstep/d7d8672e-e993-46ee-a2dd-a1a4a4786574: direct link, hf CLI and curl.
- Browser
- Download file 35.2 MB
-
https://huggingface.co/gavrilstep/d7d8672e-e993-46ee-a2dd-a1a4a4786574/resolve/d242c0ed8103db488c4fb3ccdccfdc68c27356f0/adapter_model.safetensors
- Command line
-
hf download hf://gavrilstep/d7d8672e-e993-46ee-a2dd-a1a4a4786574@d242c0ed8103db488c4fb3ccdccfdc68c27356f0/adapter_model.safetensors
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curl -L -o adapter_model.safetensors https://huggingface.co/gavrilstep/d7d8672e-e993-46ee-a2dd-a1a4a4786574/resolve/d242c0ed8103db488c4fb3ccdccfdc68c27356f0/adapter_model.safetensors
35.2 MB
- Xet hash:
- 2fe4a77b3275cd981fec83e73d00eec93ee02f9823b484aebeb1642a43f5a71f
- Size of remote file:
- 35.2 MB
- SHA256:
- f29f9c89379648b8dd161e983b9f4d03f13571a643ff69ce4b64ec915fa090c7
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