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:
- e9ce42eaff9cce1d2cef1b191c6f6d192f9c587ed4798658bd38858074da9cc1
- Size of remote file:
- 4.6 kB
- SHA256:
- 82029c8377db9305ec601f16c7bbe837a0eaae271641d71c73fcd7e0823a3d1d
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