Text Classification
Transformers
PyTorch
TensorBoard
Safetensors
bert
Generated from Trainer
text-embeddings-inference
Instructions to use lschlessinger/bert-finetuned-math-prob-classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use lschlessinger/bert-finetuned-math-prob-classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="lschlessinger/bert-finetuned-math-prob-classification")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("lschlessinger/bert-finetuned-math-prob-classification") model = AutoModelForSequenceClassification.from_pretrained("lschlessinger/bert-finetuned-math-prob-classification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
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Librarian Bot: Update Hugging Face dataset ID (#3)
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Librarian Bot: Add base_model information to model (#2)
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Adding `safetensors` variant of this model (#1)
- Adding `safetensors` variant of this model (f123427e01df66f9042fba22d3ef1da43c24f4b8) Co-authored-by: Safetensors convertbot <SFconvertbot@users.noreply.huggingface.co>33cc54c
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End of training
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Training in progress, epoch 1
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initial commit
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