Text Classification
Transformers
PyTorch
TensorBoard
Safetensors
distilbert
Generated from Trainer
text-embeddings-inference
Instructions to use rootacess/distilbert-base-uncased-finetuned-mathQA with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use rootacess/distilbert-base-uncased-finetuned-mathQA with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="rootacess/distilbert-base-uncased-finetuned-mathQA")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("rootacess/distilbert-base-uncased-finetuned-mathQA") model = AutoModelForSequenceClassification.from_pretrained("rootacess/distilbert-base-uncased-finetuned-mathQA", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Training completed!
Browse files
pytorch_model.bin
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runs/Mar06_13-28-48_ec6f311ba91e/events.out.tfevents.1678109406.ec6f311ba91e.22797.0
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