Instructions to use mtzig/reverse_add_replicate_eval17_small_1layer_d1_20 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mtzig/reverse_add_replicate_eval17_small_1layer_d1_20 with Transformers:
# Load model directly from transformers import NanoGPT model = NanoGPT.from_pretrained("mtzig/reverse_add_replicate_eval17_small_1layer_d1_20", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3493486521297465e2689b92b0d05435a7420403703e0bb308d7dbc11e21cd98
- Size of remote file:
- 1.6 kB
- SHA256:
- be36c80847e1ee287c8c4008b2197fa988e75b324747faf01148df2c1e141c6f
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.