Instructions to use Wadden/distilbert-sentiment-demo with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Wadden/distilbert-sentiment-demo with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Wadden/distilbert-sentiment-demo")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Wadden/distilbert-sentiment-demo") model = AutoModelForSequenceClassification.from_pretrained("Wadden/distilbert-sentiment-demo", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Link the interactive ONNX Space
Browse files
README.md
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classifier = pipeline("sentiment-analysis", model="Wadden/distilbert-sentiment-demo")
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classifier("This movie was fantastic!")
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classifier = pipeline("sentiment-analysis", model="Wadden/distilbert-sentiment-demo")
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classifier("This movie was fantastic!")
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## Interactive demo
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The quantized ONNX export is executed directly in the browser with Transformers.js:
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**[Open the interactive Space](https://huggingface.co/spaces/Wadden/distilbert-sentiment-space)**
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