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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1e110053f16bc04d456735e607f4c7910aa1cfde80181d66345547d8184b7fe3
- Size of remote file:
- 178 kB
- SHA256:
- 495ac548c0fcfb9382ff79ee0ba17122b1fd6fe08af8230ac27a854d6b7bd4d7
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