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, AutoModelForMultimodalLM tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-MraModel") model = AutoModelForMultimodalLM.from_pretrained("hf-internal-testing/tiny-random-MraModel") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3035ac3de24acb511906784c6b983ca42b514bc30902b4585406c7bdcff294c1
- Size of remote file:
- 178 kB
- SHA256:
- 298e3c1547b608486668479db6e9c93452cce959f4a3528d3390e40e49534c93
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