Instructions to use hf-tiny-model-private/tiny-random-FunnelForPreTraining 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-FunnelForPreTraining with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForPreTraining tokenizer = AutoTokenizer.from_pretrained("hf-tiny-model-private/tiny-random-FunnelForPreTraining") model = AutoModelForPreTraining.from_pretrained("hf-tiny-model-private/tiny-random-FunnelForPreTraining", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9506a508f324dfee49ead11259e51f4115154dab68c05954e5a5ba492e7aba40
- Size of remote file:
- 426 kB
- SHA256:
- fa61f83bb7e336286d109abcfa4e7f6284c6c9b4a0b969b120595fd0a3833cc2
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.