Instructions to use danielachacon/roberta_base_SBIC with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use danielachacon/roberta_base_SBIC with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="danielachacon/roberta_base_SBIC")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("danielachacon/roberta_base_SBIC") model = AutoModelForSequenceClassification.from_pretrained("danielachacon/roberta_base_SBIC", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from danielachacon/roberta_base_SBIC: direct link, hf CLI and curl.
- Browser
- Download file 499 MB
-
https://huggingface.co/danielachacon/roberta_base_SBIC/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://danielachacon/roberta_base_SBIC/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/danielachacon/roberta_base_SBIC/resolve/main/pytorch_model.bin
499 MB
- Xet hash:
- b1ebcfb5aa73d728b4f1fa277867bc3269c0dcaea7fa3ab944eb1ee1ef24b19d
- Size of remote file:
- 499 MB
- SHA256:
- 8645a99a00b95a4ba74a03c56fff8ddfb85d22a2a70c58bb56ba0830def4bd33
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