Text Classification
Transformers
PyTorch
distilbert
Generated from Trainer
text-embeddings-inference
Instructions to use SetFit/distilbert-base-uncased__sst2__train-16-3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SetFit/distilbert-base-uncased__sst2__train-16-3 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="SetFit/distilbert-base-uncased__sst2__train-16-3")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("SetFit/distilbert-base-uncased__sst2__train-16-3") model = AutoModelForSequenceClassification.from_pretrained("SetFit/distilbert-base-uncased__sst2__train-16-3") - Notebooks
- Google Colab
- Kaggle
Checkpoint for WandB run: distilbert__train-16-3
Browse files- training_args.bin +1 -1
training_args.bin
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