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:
- f13e76692e9457e1f53a6ca01f692729cf577c3a9195207edd8d3c106fbc16af
- Size of remote file:
- 178 kB
- SHA256:
- b3e44c3391cf053a13898184df7fdb692b115359d40aad467b4db41590fb8fd7
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