Text Classification
Transformers
PyTorch
TensorFlow
TensorBoard
distilbert
Generated from Trainer
text-embeddings-inference
Instructions to use judithrosell/seqcl with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use judithrosell/seqcl with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="judithrosell/seqcl")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("judithrosell/seqcl") model = AutoModelForSequenceClassification.from_pretrained("judithrosell/seqcl", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c66c37e25dc0237bb6c1eabad204313a02f95aef4b392bb938cfbaff7aadb58c
- Size of remote file:
- 268 MB
- SHA256:
- e8e61512a5d0e0c6916e92ec7ac4b680dbf5cb03a0ca5a4dd9b5470b650f4347
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