Instructions to use tarabukinivan/7237d99e-5040-4f58-906d-6864aa524904 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use tarabukinivan/7237d99e-5040-4f58-906d-6864aa524904 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/gemma-2-2b-it") model = PeftModel.from_pretrained(base_model, "tarabukinivan/7237d99e-5040-4f58-906d-6864aa524904") - Notebooks
- Google Colab
- Kaggle
Download adapter_model.bin from tarabukinivan/7237d99e-5040-4f58-906d-6864aa524904: direct link, hf CLI and curl.
- Browser
- Download file 41.7 MB
-
https://huggingface.co/tarabukinivan/7237d99e-5040-4f58-906d-6864aa524904/resolve/main/adapter_model.bin
- Command line
-
hf download hf://tarabukinivan/7237d99e-5040-4f58-906d-6864aa524904/adapter_model.bin
-
curl -L -o adapter_model.bin https://huggingface.co/tarabukinivan/7237d99e-5040-4f58-906d-6864aa524904/resolve/main/adapter_model.bin
41.7 MB
- Xet hash:
- 34c213d3396b31ecf9bd19c74617a4fbe0724abf8eeb38d1bdcc56d03d815b52
- Size of remote file:
- 41.7 MB
- SHA256:
- 7a19fd17d29e9b3d16989d085e9fef01a9522cb7917fa461b5f7a22ec261d937
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