Instructions to use RenderFormer/renderformer-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use RenderFormer/renderformer-v2 with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("RenderFormer/renderformer-v2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "schema_version": 1, | |
| "components": [ | |
| { | |
| "name": "transformer_512", | |
| "class": "RenderFormerModel", | |
| "pipeline_class": "RenderFormerV2Pipeline", | |
| "path": "transformer_512", | |
| "resolution": 512 | |
| }, | |
| { | |
| "name": "transformer_2048", | |
| "class": "RenderFormerModel", | |
| "pipeline_class": "RenderFormerV2Pipeline", | |
| "path": "transformer_2048", | |
| "resolution": 2048 | |
| }, | |
| { | |
| "name": "material_autoencoder", | |
| "class": "MaterialAutoencoder", | |
| "path": "material_autoencoder", | |
| "resolution": 256 | |
| }, | |
| { | |
| "name": "diffspec_mapper", | |
| "class": "DiffuseSpecularToLatent", | |
| "path": "diffspec_mapper", | |
| "resolution": null | |
| }, | |
| { | |
| "name": "metallic_mapper", | |
| "class": "PrincipledBRDFToLatent", | |
| "path": "metallic_mapper", | |
| "resolution": null | |
| }, | |
| { | |
| "name": "metallic_transmission_mapper", | |
| "class": "PrincipledBRDFToLatentWithTransmission", | |
| "path": "metallic_transmission_mapper", | |
| "resolution": null | |
| } | |
| ] | |
| } | |