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:
- 23b2111e78ecae08a48c924cadce9276d07f7bc350fd788ba657069ed592f84e
- Size of remote file:
- 5.3 kB
- SHA256:
- bd8d9e40bf1f0a8e2cd9114a0601c27119432bf397259b2f9b2081fee86c6bec
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