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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f0ce73e709d3ce3997355068a4fc63f98b901228b59f43b8e45807d017b7a295
- Size of remote file:
- 368 kB
- SHA256:
- dc97e8b38183442bc7b12e70be6cea2c14c5af5794edbabbfa63f8c3b20bca73
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