Instructions to use ModelTC/roberta-base-cola with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ModelTC/roberta-base-cola with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ModelTC/roberta-base-cola")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("ModelTC/roberta-base-cola") model = AutoModelForSequenceClassification.from_pretrained("ModelTC/roberta-base-cola", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from ModelTC/roberta-base-cola: direct link, hf CLI and curl.
- Browser
- Download file 499 MB
-
https://huggingface.co/ModelTC/roberta-base-cola/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://ModelTC/roberta-base-cola/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/ModelTC/roberta-base-cola/resolve/main/pytorch_model.bin
499 MB
- Xet hash:
- cc71b2ad6ab476518da7fbf26d6aee02191d72783a32022333c49352ca9d8207
- Size of remote file:
- 499 MB
- SHA256:
- 430376113b7f419456191f13afe5f30b1e05712113747f382aa9650abf108348
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