Text Classification
Transformers
TensorBoard
Safetensors
distilbert
Generated from Trainer
text-embeddings-inference
Instructions to use Surbhipatil/Text_Classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Surbhipatil/Text_Classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Surbhipatil/Text_Classification")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Surbhipatil/Text_Classification") model = AutoModelForSequenceClassification.from_pretrained("Surbhipatil/Text_Classification") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f8646cb0870792e9542da0060f0ad9f79d6a6c119248732500dfb4330def12d4
- Size of remote file:
- 268 MB
- SHA256:
- 94c683e27149f1fb9535cbab1fbefd2cf703e6942b852933a0cfa1f5ccc27684
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