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")# 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
Adding `safetensors` variant of this model
#1
by SFconvertbot - opened
- model.safetensors +3 -0
model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:3e2dba622b6fc9abcf8493778a6e9862f4150ac5458a9caad3a5e1ab1b64f6a7
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size 267844872
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