Text Classification
Transformers
TensorBoard
Safetensors
distilbert
Generated from Trainer
text-embeddings-inference
Instructions to use msivanes/sequence_classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use msivanes/sequence_classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="msivanes/sequence_classification")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("msivanes/sequence_classification") model = AutoModelForSequenceClassification.from_pretrained("msivanes/sequence_classification") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b3f8831865b05857702ad64b2483035dafd470761dabd9a899d4622cbecb5054
- Size of remote file:
- 4.6 kB
- SHA256:
- e4dbc28330ff3d1eeb47ff3c1a1d2252117d7646c0bd72bc3067eca30134bb46
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