Instructions to use hf-tiny-model-private/tiny-random-RoCBertForPreTraining 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-RoCBertForPreTraining with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForMultimodalLM tokenizer = AutoTokenizer.from_pretrained("hf-tiny-model-private/tiny-random-RoCBertForPreTraining") model = AutoModelForMultimodalLM.from_pretrained("hf-tiny-model-private/tiny-random-RoCBertForPreTraining") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a59977b133427f05b6c8836acd8caa9d4accc3d6de75e847da760a8262f3754a
- Size of remote file:
- 3.07 MB
- SHA256:
- 94b8ce240c3b14b67fb5d4075e1d798aa52a5dc7eac9628ceb314dc8e29de651
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