Text Classification
Transformers
Safetensors
PyTorch
English
roberta
sentiment-analysis
imdb
Eval Results (legacy)
text-embeddings-inference
Instructions to use nkadoor/sentiment-classifier-roberta with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nkadoor/sentiment-classifier-roberta with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="nkadoor/sentiment-classifier-roberta")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("nkadoor/sentiment-classifier-roberta") model = AutoModelForSequenceClassification.from_pretrained("nkadoor/sentiment-classifier-roberta") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1c43fc22140875dfffba8c9608447a0a90c5ed56af7641e0a787d7ea0dbd6def
- Size of remote file:
- 5.78 kB
- SHA256:
- 4522dd31ddcbf659796b2d2abda50e177429b543d3503af331ec1e32e1add374
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