Instructions to use hf-tiny-model-private/tiny-random-LxmertModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-tiny-model-private/tiny-random-LxmertModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="hf-tiny-model-private/tiny-random-LxmertModel")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("hf-tiny-model-private/tiny-random-LxmertModel") model = AutoModel.from_pretrained("hf-tiny-model-private/tiny-random-LxmertModel") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 656ab7f58da874466e292dd6440c6d62f818e81cecc71e345a3129598835d397
- Size of remote file:
- 387 kB
- SHA256:
- a14b2f5e55e51f8d3103cd6c06d0ef08ff1763d691c395c2adb435fd67d16835
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