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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4c468d2d14a68d8a74d637628f1fe38447e1ad3a3791e7f8639773b7cc20c33c
- Size of remote file:
- 3.07 MB
- SHA256:
- 6aef23c0d3e806153a53400c3dfbcd07f173f2d5bef8fbd2c688ad570bcae36f
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