Instructions to use hf-internal-testing/tiny-random-LxmertModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-LxmertModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="hf-internal-testing/tiny-random-LxmertModel")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-LxmertModel") model = AutoModel.from_pretrained("hf-internal-testing/tiny-random-LxmertModel", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2a78c9937fe677b4519ae2dce004fb48d9f293bec2be50b8527f11838c6faf23
- Size of remote file:
- 368 kB
- SHA256:
- 6f17170a96d2011c240186a9fc3d589c3941771f07a84162c363ac3d0210a659
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