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:
- eda565b0c4536b092336e2c5596ffbd86f866ff1563485e1b0fe37a9d365d117
- Size of remote file:
- 499 kB
- SHA256:
- 79319a7b3ea9b34ce10cb7d58db4b47ce2b681bb74302235372e66d77e50ca1c
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