Instructions to use Howard001/roberta-large-lora-token-classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use Howard001/roberta-large-lora-token-classification with PEFT:
from peft import PeftModel from transformers import AutoModelForTokenClassification base_model = AutoModelForTokenClassification.from_pretrained("roberta-large") model = PeftModel.from_pretrained(base_model, "Howard001/roberta-large-lora-token-classification") - Notebooks
- Google Colab
- Kaggle
Download adapter_model.bin from Howard001/roberta-large-lora-token-classification: direct link, hf CLI and curl.
- Browser
- Download file 7.52 MB
-
https://huggingface.co/Howard001/roberta-large-lora-token-classification/resolve/main/adapter_model.bin
- Command line
-
hf download hf://Howard001/roberta-large-lora-token-classification/adapter_model.bin
-
curl -L -o adapter_model.bin https://huggingface.co/Howard001/roberta-large-lora-token-classification/resolve/main/adapter_model.bin
7.52 MB
- Xet hash:
- 586e17256e4c89257205e816a5406c74cdf66db5e7eaae19e6c084c2aaae952d
- Size of remote file:
- 7.52 MB
- SHA256:
- f42315db697166afc2c27a97c1f48797c4f745863d1749502ac9e8795e63d99a
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.