Instructions to use hf-internal-testing/tiny-random-RoCBertForPreTraining with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-RoCBertForPreTraining with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForPreTraining tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-RoCBertForPreTraining") model = AutoModelForPreTraining.from_pretrained("hf-internal-testing/tiny-random-RoCBertForPreTraining") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8870662a238ecc6e3aa1ba3d451d05e7f1211063a6c74d4571bd44b23ea38c36
- Size of remote file:
- 3.05 MB
- SHA256:
- 3e24d124be7492b8c7d0f8467214f416f949355430ef67fa09eb884160dc1ec5
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