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:
- 8e9eb4831e7cdce816dbf2d2020950ea07bdb687f7cb007286a1f5cff24b8c11
- Size of remote file:
- 3.38 kB
- SHA256:
- 4d7962943e1c6482c9b400211108349a268e073d4cce3369eb807759d53e8f12
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