Instructions to use microsoft/Lens-Base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use microsoft/Lens-Base with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("microsoft/Lens-Base", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
| { | |
| "_class_name": "LensTransformer2DModel", | |
| "_diffusers_version": "0.37.1", | |
| "attention_head_dim": 64, | |
| "axes_dims_rope": [ | |
| 8, | |
| 28, | |
| 28 | |
| ], | |
| "enc_hidden_dim": 2880, | |
| "gate_mlp": true, | |
| "in_channels": 128, | |
| "inner_dim": 1536, | |
| "multi_layer_encoder_feature": true, | |
| "num_attention_heads": 24, | |
| "num_layers": 48, | |
| "out_channels": 32, | |
| "patch_size": 2, | |
| "rms_norm": true, | |
| "selected_layer_index": [ | |
| 5, | |
| 11, | |
| 17, | |
| 23 | |
| ] | |
| } | |