Text Classification
Transformers
PyTorch
distilbert
Generated from Trainer
text-embeddings-inference
Instructions to use SetFit/distilbert-base-uncased__subj__all-train with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SetFit/distilbert-base-uncased__subj__all-train with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="SetFit/distilbert-base-uncased__subj__all-train")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("SetFit/distilbert-base-uncased__subj__all-train") model = AutoModelForSequenceClassification.from_pretrained("SetFit/distilbert-base-uncased__subj__all-train") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7d588991189fa3ddea48fb7eddbbc4f44c387cf0c0696a2fe359773cf574e157
- Size of remote file:
- 268 MB
- SHA256:
- e2d07b2882402f58acfe8c80ea8c00ab4b8442ea938a520c1dc32359abaa18f8
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