Instructions to use hf-internal-testing/tiny-random-FunnelForPreTraining with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-FunnelForPreTraining with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForPreTraining tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-FunnelForPreTraining") model = AutoModelForPreTraining.from_pretrained("hf-internal-testing/tiny-random-FunnelForPreTraining", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 79ff6774bc553c8227521da97216b08a14994a43f95b833beff955221e904173
- Size of remote file:
- 342 kB
- SHA256:
- 1ae124ed314dc8d018c7cfab0cd8470214a3de67d9b3f061bef3ddbb0bd66925
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.