Instructions to use vdos/702daad2-31e6-4ed8-9647-43c4a17482bb with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use vdos/702daad2-31e6-4ed8-9647-43c4a17482bb with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/gemma-2b-it") model = PeftModel.from_pretrained(base_model, "vdos/702daad2-31e6-4ed8-9647-43c4a17482bb") - Notebooks
- Google Colab
- Kaggle
Download adapter_model.bin from vdos/702daad2-31e6-4ed8-9647-43c4a17482bb: direct link, hf CLI and curl.
- Browser
- Download file 157 MB
-
https://huggingface.co/vdos/702daad2-31e6-4ed8-9647-43c4a17482bb/resolve/main/adapter_model.bin
- Command line
-
hf download hf://vdos/702daad2-31e6-4ed8-9647-43c4a17482bb/adapter_model.bin
-
curl -L -o adapter_model.bin https://huggingface.co/vdos/702daad2-31e6-4ed8-9647-43c4a17482bb/resolve/main/adapter_model.bin
157 MB
- Xet hash:
- 050bc4f094665a520310ab67fe12f828f5e886b6e8fa85944011644e18e85301
- Size of remote file:
- 157 MB
- SHA256:
- 3d32ca0a161867e1d5a0f0c48a37f5fd532c2ef104a4b4f4fcdfc080742fc15d
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