Instructions to use ghe1231/mrpc with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ghe1231/mrpc with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ghe1231/mrpc")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("ghe1231/mrpc") model = AutoModelForSequenceClassification.from_pretrained("ghe1231/mrpc", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download flax_model.msgpack from ghe1231/mrpc: direct link, hf CLI and curl.
- Browser
- Download file 433 MB
-
https://huggingface.co/ghe1231/mrpc/resolve/main/flax_model.msgpack
- Command line
-
hf download hf://ghe1231/mrpc/flax_model.msgpack
-
curl -L -o flax_model.msgpack https://huggingface.co/ghe1231/mrpc/resolve/main/flax_model.msgpack
433 MB
- Xet hash:
- 1e73e31e71a45e87e5f182f0c5262e5e2ff057237865c8f2df334ca0c2ff6bc0
- Size of remote file:
- 433 MB
- SHA256:
- 05d9e3cfcfc4d42caabcd874e8c1d19ee63c3bbee6bb72e3c9fe9f6ef6bf3d94
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