Text Classification
Transformers
PyTorch
TensorBoard
distilbert
Generated from Trainer
text-embeddings-inference
Instructions to use padmajabfrl/Religion-Classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use padmajabfrl/Religion-Classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="padmajabfrl/Religion-Classification")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("padmajabfrl/Religion-Classification") model = AutoModelForSequenceClassification.from_pretrained("padmajabfrl/Religion-Classification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7238d64793e1b973cdcb461747b104eb3791ca401f621948dbdda6cda6cf1dbb
- Size of remote file:
- 268 MB
- SHA256:
- d0c6835aef32720b764f3b1b2aacdb8a69aa94c77c83236f02d4478852f6cf96
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