Text Classification
Transformers
PyTorch
TensorFlow
Rust
ONNX
Safetensors
English
distilbert
Eval Results (legacy)
Instructions to use distilbert/distilbert-base-uncased-finetuned-sst-2-english with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use distilbert/distilbert-base-uncased-finetuned-sst-2-english with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="distilbert/distilbert-base-uncased-finetuned-sst-2-english")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("distilbert/distilbert-base-uncased-finetuned-sst-2-english") model = AutoModelForSequenceClassification.from_pretrained("distilbert/distilbert-base-uncased-finetuned-sst-2-english") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1f960ab174a89eb4fb5f669330a78ef1b555d786cb3492f6cf6e527f119921f8
- Size of remote file:
- 268 MB
- SHA256:
- b44df675bb34ccd8e57c14292c811ac7358b7c8e37c7f212745f640cd6019ac8
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