Text Classification
Transformers
PyTorch
TensorBoard
distilbert
Generated from Trainer
Eval Results (legacy)
text-embeddings-inference
Instructions to use ManishW/text-classification-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ManishW/text-classification-model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ManishW/text-classification-model")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("ManishW/text-classification-model") model = AutoModelForSequenceClassification.from_pretrained("ManishW/text-classification-model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c42fbf9f36203459e107fb1c2dfc36e932b26b8c669be990eeeedf57f7cf31a8
- Size of remote file:
- 3.64 kB
- SHA256:
- 69ea01b7f9d3d291dc28f39ed42d039d9b225162e4d2cc5bc02d7117d533dfde
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