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:
- fdfe005e8f5da6c6c7055e86bee187bfa784ce1003467a76fe11f6776da3417b
- Size of remote file:
- 268 MB
- SHA256:
- 85f030c724e14f9f6853bfc03d9fc2105e9943bce5053fc99a257db70306f253
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