Text Classification
Transformers
TensorBoard
Safetensors
distilbert
Generated from Trainer
Eval Results (legacy)
text-embeddings-inference
Instructions to use dinhlnd1610/distilbert-base-uncased-finetuned-sst2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dinhlnd1610/distilbert-base-uncased-finetuned-sst2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="dinhlnd1610/distilbert-base-uncased-finetuned-sst2")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("dinhlnd1610/distilbert-base-uncased-finetuned-sst2") model = AutoModelForSequenceClassification.from_pretrained("dinhlnd1610/distilbert-base-uncased-finetuned-sst2") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9056a5e0ebd9c1690b4e98c986f60a61722fad6c4f6607350bfecda302b5844e
- Size of remote file:
- 4.6 kB
- SHA256:
- d4762d2ccec83ca7d57c8fa923c3c8c6f444fa1fa1bda1b41929c3843bd52432
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