Image-to-Image
Transformers
Safetensors
fela_pde_fno2d
feature-extraction
fela
fourier-neural-operator
fno
cpu
on-device
pde-surrogate
thermal-simulation
battery
custom_code
Instructions to use lowdown-labs/fela-pde with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use lowdown-labs/fela-pde with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-to-image", model="lowdown-labs/fela-pde", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("lowdown-labs/fela-pde", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "model": "pde", | |
| "format": "fp16-streaming", | |
| "note": "load order is smallest-first for progressive/streaming load", | |
| "files": [ | |
| { | |
| "file": "model_fp16.safetensors", | |
| "source": "model.safetensors", | |
| "dtype": "fp16", | |
| "bytes": 3555962, | |
| "approx_mb": 3.391 | |
| } | |
| ] | |
| } |