Text Classification
Transformers
PyTorch
Safetensors
distilbert
Eval Results (legacy)
text-embeddings-inference
Instructions to use DracoHugging/Distilbert-sentiment-analysis with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use DracoHugging/Distilbert-sentiment-analysis with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="DracoHugging/Distilbert-sentiment-analysis")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("DracoHugging/Distilbert-sentiment-analysis") model = AutoModelForSequenceClassification.from_pretrained("DracoHugging/Distilbert-sentiment-analysis", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ea7bf487f85483300f9c7408b47b783de5379573c1d088a1abf675e6582f6980
- Size of remote file:
- 268 MB
- SHA256:
- a00d166a771f3c4f26435419203556734607cd07b24f8b2c572301e7a3a23ce2
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