Instructions to use hf-internal-testing/tiny-random-MraModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-MraModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="hf-internal-testing/tiny-random-MraModel")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-MraModel") model = AutoModel.from_pretrained("hf-internal-testing/tiny-random-MraModel") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 07eae88b952abb8ac5ac2946d84fae59292fe8df14deb73c93718da366f1c292
- Size of remote file:
- 178 kB
- SHA256:
- 2379e08b8837ee9722b2b3e45850f6e37bd7c9d5a921ac4ff0aaa418d984a307
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