Instructions to use joonhan/roberta-roa with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use joonhan/roberta-roa with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="joonhan/roberta-roa")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("joonhan/roberta-roa") model = AutoModelForTokenClassification.from_pretrained("joonhan/roberta-roa", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from joonhan/roberta-roa: direct link, hf CLI and curl.
- Browser
- Download file 1.34 GB
-
https://huggingface.co/joonhan/roberta-roa/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://joonhan/roberta-roa/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/joonhan/roberta-roa/resolve/main/pytorch_model.bin
1.34 GB
- Xet hash:
- 3db94aa2794fd30b75674252deaa11c9e74c097b7c2a0eae01e6000e564290a6
- Size of remote file:
- 1.34 GB
- SHA256:
- 433cddc94d838fb10182e2a401a4f825916d5d37d4348ec4b9d41f35514dddc7
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