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 pytorch_model.bin from mattchurgin/distilbert-mrpc: direct link, hf CLI and curl.
- Browser
- Download file 268 MB
-
https://huggingface.co/mattchurgin/distilbert-mrpc/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://mattchurgin/distilbert-mrpc/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/mattchurgin/distilbert-mrpc/resolve/main/pytorch_model.bin
268 MB
- Xet hash:
- a7a77e4f19cf91c685f9104cc779c6b1df86f7425a5cdd434e5440b3a95c047c
- Size of remote file:
- 268 MB
- SHA256:
- 5ae89679442166e82608d037e33b4a8dd0b1ea592c6773dc7badff55f8e92c30
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