Text Classification
Transformers
PyTorch
distilbert
Generated from Trainer
Eval Results (legacy)
text-embeddings-inference
Instructions to use mattchurgin/distilbert-mrpc with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mattchurgin/distilbert-mrpc with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="mattchurgin/distilbert-mrpc")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("mattchurgin/distilbert-mrpc") model = AutoModelForSequenceClassification.from_pretrained("mattchurgin/distilbert-mrpc", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from mattchurgin/distilbert-mrpc: direct link, hf CLI and curl.
- Browser
- Download file 2.93 kB
-
https://huggingface.co/mattchurgin/distilbert-mrpc/resolve/main/training_args.bin
- Command line
-
hf download hf://mattchurgin/distilbert-mrpc/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/mattchurgin/distilbert-mrpc/resolve/main/training_args.bin
2.93 kB
- Xet hash:
- 513ab2d990a23efa572b3106761f2806183246b046a53de2eca8dd59d41b9435
- Size of remote file:
- 2.93 kB
- SHA256:
- 3d18e316ff2e90b45d395db5e85da42983bd5a09ef051e697a5be30172ced909
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