Text Classification
Transformers
TensorBoard
Safetensors
roberta
Generated from Trainer
text-embeddings-inference
Instructions to use benmanks/sentiment_analysis with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use benmanks/sentiment_analysis with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="benmanks/sentiment_analysis")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("benmanks/sentiment_analysis") model = AutoModelForSequenceClassification.from_pretrained("benmanks/sentiment_analysis", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 38aa00e61b8f2a3dd71489dd3b14bbf6e5e0825bcefac40a62dabc32a25a45e0
- Size of remote file:
- 499 MB
- SHA256:
- 76a5bafaa026168096d9169cdea8dc86d8306cba147c02ae81375d42b296973d
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