Text Classification
Transformers
PyTorch
TensorBoard
bert
Generated from Trainer
Eval Results (legacy)
text-embeddings-inference
Instructions to use xysmalobia/sequence_classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use xysmalobia/sequence_classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="xysmalobia/sequence_classification")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("xysmalobia/sequence_classification") model = AutoModelForSequenceClassification.from_pretrained("xysmalobia/sequence_classification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
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Librarian Bot: Add base_model information to model (#2)
- Librarian Bot: Add base_model information to model (32611e5aad92a6bf68e13f719599ee0ea45796e8) Co-authored-by: Librarian Bot (Bot) <librarian-bot@users.noreply.huggingface.co>5c87493
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update model card README.md
1ad5020 -
End of training
9ef8515 -
Training in progress, step 500
d6488cd -
initial commit
8e9d55b