Instructions to use andrewheins55/Ming-flash-omni-2.1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use andrewheins55/Ming-flash-omni-2.1 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("andrewheins55/Ming-flash-omni-2.1", 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
| { | |
| "aggregator": { | |
| "attn_backend": "torch", | |
| "attn_mask_enabled": false, | |
| "depth": 8, | |
| "dropout": 0.1, | |
| "hidden_size": 1024, | |
| "in_channels": 64, | |
| "mlp_ratio": 4, | |
| "num_heads": 16, | |
| "pe_attn_head": null, | |
| "qk_norm": null | |
| }, | |
| "architectures": [ | |
| "BailingTalker2" | |
| ], | |
| "cfg_strength": 2.0, | |
| "flowmodel": { | |
| "attn_backend": "torch", | |
| "attn_mask_enabled": false, | |
| "depth": 8, | |
| "dropout": 0, | |
| "hidden_size": 1024, | |
| "in_channels": 64, | |
| "mlp_ratio": 4, | |
| "num_heads": 16, | |
| "pe_attn_head": null, | |
| "qk_norm": null | |
| }, | |
| "history_patch_size": 32, | |
| "patch_size": 4, | |
| "steps": 10, | |
| "torch_dtype": "bfloat16", | |
| "transformers_version": "4.51.3" | |
| } | |