Text Classification
Transformers
PyTorch
TensorBoard
distilbert
Generated from Trainer
Eval Results (legacy)
text-embeddings-inference
Instructions to use pulkitmehtawork/text_classification_pulkit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use pulkitmehtawork/text_classification_pulkit with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="pulkitmehtawork/text_classification_pulkit")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("pulkitmehtawork/text_classification_pulkit") model = AutoModelForSequenceClassification.from_pretrained("pulkitmehtawork/text_classification_pulkit") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 50b783c27ef8424e000b993d355ffd0bd58af200ef651c6c82a7be4bcd7415b9
- Size of remote file:
- 268 MB
- SHA256:
- c0b7e8a63a8394aea67670f4e453673e04475076df31eb2dd9298ef23d0cadc2
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