Text Classification
Transformers
PyTorch
TensorBoard
distilbert
Generated from Trainer
text-embeddings-inference
Instructions to use padmajabfrl/Religion-Classification-Custom-Model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use padmajabfrl/Religion-Classification-Custom-Model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="padmajabfrl/Religion-Classification-Custom-Model")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("padmajabfrl/Religion-Classification-Custom-Model") model = AutoModelForSequenceClassification.from_pretrained("padmajabfrl/Religion-Classification-Custom-Model") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a5596ae44c5adbc6d01c9c1ff8bd48503909486f503cd4a5a2a22afd40d8d5e9
- Size of remote file:
- 3.96 kB
- SHA256:
- b3bf75e1b06c08dd8493493cd559d57162620021ab8f4f38eb62e7fd34000a27
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