Instructions to use KotshinZ/gpt2-RMT-2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use KotshinZ/gpt2-RMT-2 with Transformers:
# Load model directly from transformers import RecurrentMemoryTransformer model = RecurrentMemoryTransformer.from_pretrained("KotshinZ/gpt2-RMT-2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a65c47aba547475ee52f711a6de4c474d6e79bb9333c64d95e56d8d78ffb747a
- Size of remote file:
- 7.35 kB
- SHA256:
- 88757a2b8b1c49ba8b8f97161dacdb95ca6b6fd7a56d93df7f7c1df11e238bd7
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.