Text Classification
Transformers
PyTorch
TensorBoard
distilbert
Generated from Trainer
Eval Results (legacy)
text-embeddings-inference
Instructions to use danlupu/sentiment-analysis with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use danlupu/sentiment-analysis with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="danlupu/sentiment-analysis")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("danlupu/sentiment-analysis") model = AutoModelForSequenceClassification.from_pretrained("danlupu/sentiment-analysis", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 68a52979ac3a57acaa6bcce4489011444e497fce8fa7d8cb338e83ef05ad0d09
- Size of remote file:
- 268 MB
- SHA256:
- d9908db1fc361759e673e2f2391a4d0a209a71afb3dc629ec6ec1942dd790cc8
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