Instructions to use tmills/roberta_sfda_sharpseed with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tmills/roberta_sfda_sharpseed with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="tmills/roberta_sfda_sharpseed")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("tmills/roberta_sfda_sharpseed") model = AutoModelForSequenceClassification.from_pretrained("tmills/roberta_sfda_sharpseed") - Notebooks
- Google Colab
- Kaggle
Update pytorch_model.bin
Browse files- pytorch_model.bin +3 -0
pytorch_model.bin
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version https://git-lfs.github.com/spec/v1
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oid sha256:b2af9c98f6fffb979fc579c86f9bb8742c32fca3e5d62f3dac9c9bf6e183a349
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size 501013463
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