Instructions to use mtzig/reverse_add_replicate_eval17_small_1layer_d1_50 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_50 with Transformers:
# Load model directly from transformers import NanoGPT model = NanoGPT.from_pretrained("mtzig/reverse_add_replicate_eval17_small_1layer_d1_50", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a4789c9da2d9bda90136c16235a9746d123e95837725fb94985e09d43c9e0ab9
- Size of remote file:
- 5.3 kB
- SHA256:
- 554ce58242da689c9e3061a32d32d9ce7a48edf59855d2c97f3b8bbf0be48089
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.