Instructions to use ybelkada/test-opt-lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use ybelkada/test-opt-lora with PEFT:
from peft import PeftModel from transformers import AutoModelForSequenceClassification base_model = AutoModelForSequenceClassification.from_pretrained("facebook/opt-350m") model = PeftModel.from_pretrained(base_model, "ybelkada/test-opt-lora") - Notebooks
- Google Colab
- Kaggle
Download adapter_model.bin from ybelkada/test-opt-lora: direct link, hf CLI and curl.
- Browser
- Download file 6.33 MB
-
https://huggingface.co/ybelkada/test-opt-lora/resolve/main/adapter_model.bin
- Command line
-
hf download hf://ybelkada/test-opt-lora/adapter_model.bin
-
curl -L -o adapter_model.bin https://huggingface.co/ybelkada/test-opt-lora/resolve/main/adapter_model.bin
6.33 MB
- Xet hash:
- e89b4a1cd1aaacf6fe9873191ccd960ad604ab61e786db78d198dfdbdc7f2f0e
- Size of remote file:
- 6.33 MB
- SHA256:
- 12b261db52ad211a2b22117c7901ecbdb8a721f43740c76e504a4f05774a2c77
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