Instructions to use NTUYG/DeepSCC-RoBERTa with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use NTUYG/DeepSCC-RoBERTa with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="NTUYG/DeepSCC-RoBERTa")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("NTUYG/DeepSCC-RoBERTa") model = AutoModelForSequenceClassification.from_pretrained("NTUYG/DeepSCC-RoBERTa", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit ·
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Parent(s): 0b26093
upload flax model
Browse files- flax_model.msgpack +3 -0
flax_model.msgpack
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version https://git-lfs.github.com/spec/v1
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oid sha256:26bbe1922aacc201ebf7cf691366fe6e559cbdfcef5f279716c6ea9d6e7f3e27
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size 498648193
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