Instructions to use hf-internal-testing/tiny-random-LxmertForQuestionAnswering with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-LxmertForQuestionAnswering with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="hf-internal-testing/tiny-random-LxmertForQuestionAnswering")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-LxmertForQuestionAnswering") model = AutoModelForQuestionAnswering.from_pretrained("hf-internal-testing/tiny-random-LxmertForQuestionAnswering", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 598e2526b31b37f70b9f15027b71e30b53bb1195a2ff29e0c6d6ac9133285e5f
- Size of remote file:
- 403 kB
- SHA256:
- 75b534f7b49f91c3da424998ee0c8f9f86ae4e37368bcf3177ab4e849bd96213
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