Text Classification
Transformers
PyTorch
distilbert
Generated from Trainer
text-embeddings-inference
Instructions to use poooj/DistilBERTForClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use poooj/DistilBERTForClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="poooj/DistilBERTForClassification")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("poooj/DistilBERTForClassification") model = AutoModelForSequenceClassification.from_pretrained("poooj/DistilBERTForClassification") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- addce5156d9d795e9879d533b1796203f16ae4cdd98675ec24de5e10e7b9798f
- Size of remote file:
- 268 MB
- SHA256:
- 25cdd3f587a04107298d86463a195929e614c9ba105dca52ac8697001f5f644d
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.