Text Classification
Transformers
PyTorch
TensorBoard
distilbert
Generated from Trainer
text-embeddings-inference
Instructions to use Sandipan1994/proof_eval2-distilbert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Sandipan1994/proof_eval2-distilbert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Sandipan1994/proof_eval2-distilbert")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Sandipan1994/proof_eval2-distilbert") model = AutoModelForSequenceClassification.from_pretrained("Sandipan1994/proof_eval2-distilbert") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- fc3c2b25a1216c3f8bddbbb29ce872e72412c172e5ed872084e0a2d8ffe3035a
- Size of remote file:
- 268 MB
- SHA256:
- bdd71520b3972d8e170de5e5af74894a799d03c7821c9f826bcb3362a1c0f4a5
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