Any-to-Any
Transformers
Safetensors
nlduni
feature-extraction
custom_code
image-text-to-text
text-to-image
image-to-image
Instructions to use nvidia/NLD-Uni with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nvidia/NLD-Uni with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("nvidia/NLD-Uni", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tree_metadata.json from nvidia/NLD-Uni: direct link, hf CLI and curl.
- Browser
- Download file 207 Bytes
-
https://huggingface.co/nvidia/NLD-Uni/resolve/main/tree_metadata.json
- Command line
-
hf download hf://nvidia/NLD-Uni/tree_metadata.json
-
curl -L -o tree_metadata.json https://huggingface.co/nvidia/NLD-Uni/resolve/main/tree_metadata.json
207 Bytes
| { | |
| "filename": "pca_tree.pt", | |
| "algorithm": "recursive_centered_pca_rank_median_v1", | |
| "sha256": "4b7ee94fbb10fd4146a4ad167b595b037e3f591eaa12ecf3f0b411c82384a714", | |
| "vocab_size": 131072, | |
| "depth": 17 | |
| } | |