Text Classification
Transformers
PyTorch
distilbert
Generated from Trainer
text-embeddings-inference
Instructions to use SetFit/distilbert-base-uncased__subj__train-8-9 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SetFit/distilbert-base-uncased__subj__train-8-9 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="SetFit/distilbert-base-uncased__subj__train-8-9")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("SetFit/distilbert-base-uncased__subj__train-8-9") model = AutoModelForSequenceClassification.from_pretrained("SetFit/distilbert-base-uncased__subj__train-8-9") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ebf054bb82175cde7fbf710c43318273c38887869f91463750c030830ac3f6df
- Size of remote file:
- 268 MB
- SHA256:
- 1c4ef67ce56334b3151d1ead80675b2e690b536eedfaf5f914373078cd41eb97
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