Instructions to use nqs-models/ising_fnqs with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nqs-models/ising_fnqs with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("nqs-models/ising_fnqs", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download config.json from nqs-models/ising_fnqs: direct link, hf CLI and curl.
- Browser
- Download file 388 Bytes
-
https://huggingface.co/nqs-models/ising_fnqs/resolve/main/config.json
- Command line
-
hf download hf://nqs-models/ising_fnqs/config.json
-
curl -L -o config.json https://huggingface.co/nqs-models/ising_fnqs/resolve/main/config.json
388 Bytes
| { | |
| "L_eff": 25, | |
| "architectures": [ | |
| "NQSModel" | |
| ], | |
| "auto_map": { | |
| "AutoConfig": "vit_fnqs_config.ViTFNQSConfig", | |
| "FlaxAutoModel": "vit_fnqs_model.ViTFNQSModel" | |
| }, | |
| "b": 4, | |
| "complex": false, | |
| "d_model": 72, | |
| "disorder": false, | |
| "heads": 12, | |
| "model_type": "vit_fnqs", | |
| "num_layers": 6, | |
| "transformers_version": "4.48.0", | |
| "tras_inv": true, | |
| "two_dim": false | |
| } | |