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:
- ae5c0e305fe4b72fdc32050f108180a57506d9873d0a38811724f98cb205e411
- Size of remote file:
- 178 kB
- SHA256:
- b890b412daaa69cb6f89fc211cd7934497a623d4f3cedcb71ab17a7210e2ee7a
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