Instructions to use zhijiangknight/mrpc with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use zhijiangknight/mrpc with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="zhijiangknight/mrpc")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("zhijiangknight/mrpc") model = AutoModelForSequenceClassification.from_pretrained("zhijiangknight/mrpc", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download flax_model.msgpack from zhijiangknight/mrpc: direct link, hf CLI and curl.
- Browser
- Download file 433 MB
-
https://huggingface.co/zhijiangknight/mrpc/resolve/main/flax_model.msgpack
- Command line
-
hf download hf://zhijiangknight/mrpc/flax_model.msgpack
-
curl -L -o flax_model.msgpack https://huggingface.co/zhijiangknight/mrpc/resolve/main/flax_model.msgpack
433 MB
- Xet hash:
- ee38b418cc324a0e2a6f711b542ab530577d41b16a899f3d47b6bb663243e1e1
- Size of remote file:
- 433 MB
- SHA256:
- e67a0e8976f62f9d21447e78273a6959a16f58ec3746d1c1c8765073232a47af
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