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:
- e4098c360aad2c12a90f1aa761037d8ca8aef8f5556359e127451528509adce2
- Size of remote file:
- 268 MB
- SHA256:
- 451fbc752d626a62ab4a7545047b0334526ae33712a1d956c567ff6a179340d8
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