Instructions to use hf-internal-testing/tiny-random-BrosModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-BrosModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="hf-internal-testing/tiny-random-BrosModel")# Load model directly from transformers import AutoProcessor, AutoModel processor = AutoProcessor.from_pretrained("hf-internal-testing/tiny-random-BrosModel") model = AutoModel.from_pretrained("hf-internal-testing/tiny-random-BrosModel", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f3b4d196ce01f252d2710794be390eeb7034d1ea2ab35ae73cbc0bcf3b56ec1e
- Size of remote file:
- 908 kB
- SHA256:
- 3efba63d874e193548ad750369f45273527bfbf48ccfcced725a22cc25d6666d
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