Instructions to use hf-internal-testing/tiny-random-MPNetForMultipleChoice with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-MPNetForMultipleChoice with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForMultipleChoice tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-MPNetForMultipleChoice") model = AutoModelForMultipleChoice.from_pretrained("hf-internal-testing/tiny-random-MPNetForMultipleChoice") - Notebooks
- Google Colab
- Kaggle
[Awaiting approval] Upload ONNX weights
Browse files[Automated] Converted using [Optimum](https://github.com/huggingface/optimum). Models will be merged manually by @Xenova once they have been checked with [Transformers.js](https://github.com/xenova/transformers.js).
- onnx/model.onnx +3 -0
onnx/model.onnx
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version https://git-lfs.github.com/spec/v1
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oid sha256:9d18361de2f35c6a2cc89ea586031df5756577ab496b2197170ff6b56a4982f0
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size 1052337
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