Instructions to use tarabukinivan/b2f31e98-cc78-4404-9a42-7aa45e01ae0e with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use tarabukinivan/b2f31e98-cc78-4404-9a42-7aa45e01ae0e with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("NousResearch/Hermes-2-Pro-Mistral-7B") model = PeftModel.from_pretrained(base_model, "tarabukinivan/b2f31e98-cc78-4404-9a42-7aa45e01ae0e") - Notebooks
- Google Colab
- Kaggle
Download adapter_model.safetensors from tarabukinivan/b2f31e98-cc78-4404-9a42-7aa45e01ae0e: direct link, hf CLI and curl.
- Browser
- Download file 168 MB
-
https://huggingface.co/tarabukinivan/b2f31e98-cc78-4404-9a42-7aa45e01ae0e/resolve/main/adapter_model.safetensors
- Command line
-
hf download hf://tarabukinivan/b2f31e98-cc78-4404-9a42-7aa45e01ae0e/adapter_model.safetensors
-
curl -L -o adapter_model.safetensors https://huggingface.co/tarabukinivan/b2f31e98-cc78-4404-9a42-7aa45e01ae0e/resolve/main/adapter_model.safetensors
168 MB
- Xet hash:
- 811d377464fe86a4c3709a57095a8f696b7bb19d374ba090b61b510f8ee2e932
- Size of remote file:
- 168 MB
- SHA256:
- 264fb80c3a7830c9942425211af6bdc69e6bc596276a815cc422cd6c999f2d33
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