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:
- 005eb4a1780dcdecddeb1c22f0bf2b4472269bfda651855ca2e939e35c166c3a
- Size of remote file:
- 3.58 kB
- SHA256:
- 1140b624b5c5189f979ab26734b31d3ee229b4283551a89f4a9be7ea804efce8
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