Text Classification
Transformers
TensorBoard
Safetensors
bert
Generated from Trainer
text-embeddings-inference
Instructions to use Sandhya2002/Sentimental-bert-based-uncased with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Sandhya2002/Sentimental-bert-based-uncased with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Sandhya2002/Sentimental-bert-based-uncased")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Sandhya2002/Sentimental-bert-based-uncased") model = AutoModelForSequenceClassification.from_pretrained("Sandhya2002/Sentimental-bert-based-uncased") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- bc1343d990290679260209cf199a9559958138c6d4c62d69d869669881af17c5
- Size of remote file:
- 438 MB
- SHA256:
- 1953ac68357e7636ae0e8365f10b43bab740afdc1f530109adcdab0a8d74cb33
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