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, AutoModelForMultimodalLM tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-LxmertModel") model = AutoModelForMultimodalLM.from_pretrained("hf-internal-testing/tiny-random-LxmertModel") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 45ff322464031b4db5e5a55082d7cefeb73eba75cbf0cc3a2ed81cbc61798468
- Size of remote file:
- 387 kB
- SHA256:
- daaecf823ef0e359059fa60cf906793815bfe2c92fcc282a0121919732b70f07
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