Instructions to use WaveCut/Anima-Preview-3-SDNQ-uint4-diffusers with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use WaveCut/Anima-Preview-3-SDNQ-uint4-diffusers with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("WaveCut/Anima-Preview-3-SDNQ-uint4-diffusers", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Cosmos
How to use WaveCut/Anima-Preview-3-SDNQ-uint4-diffusers with Cosmos:
# No code snippets available yet for this library. # To use this model, check the repository files and the library's documentation. # Want to help? PRs adding snippets are welcome at: # https://github.com/huggingface/huggingface.js
- Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
| { | |
| "_class_name": "CosmosTransformer3DModel", | |
| "_diffusers_version": "0.38.0", | |
| "adaln_lora_dim": 256, | |
| "attention_head_dim": 128, | |
| "concat_padding_mask": true, | |
| "controlnet_block_every_n": null, | |
| "crossattn_proj_in_channels": 1024, | |
| "encoder_hidden_states_channels": 1024, | |
| "extra_pos_embed_type": null, | |
| "img_context_dim_in": null, | |
| "img_context_dim_out": 2048, | |
| "img_context_num_tokens": 256, | |
| "in_channels": 16, | |
| "max_size": [ | |
| 128, | |
| 240, | |
| 240 | |
| ], | |
| "mlp_ratio": 4.0, | |
| "num_attention_heads": 16, | |
| "num_layers": 28, | |
| "out_channels": 16, | |
| "patch_size": [ | |
| 1, | |
| 2, | |
| 2 | |
| ], | |
| "quantization_config": { | |
| "add_skip_keys": false, | |
| "dequantize_fp32": false, | |
| "dynamic_loss_threshold": null, | |
| "group_size": 0, | |
| "is_integer": true, | |
| "is_training": false, | |
| "modules_dtype_dict": {}, | |
| "modules_quant_config": {}, | |
| "modules_to_not_convert": [ | |
| "crossattn_proj", | |
| "patch_embed", | |
| "transformer_blocks.0.norm*", | |
| "norm_out", | |
| "proj_out", | |
| "learnable_pos_embed", | |
| "time_embed" | |
| ], | |
| "non_blocking": false, | |
| "quant_conv": false, | |
| "quant_embedding": false, | |
| "quant_method": "sdnq", | |
| "quantization_device": null, | |
| "quantized_matmul_dtype": null, | |
| "return_device": null, | |
| "sdnq_version": "0.1.8", | |
| "svd_rank": 32, | |
| "svd_steps": 8, | |
| "use_dynamic_quantization": false, | |
| "use_grad_ckpt": true, | |
| "use_quantized_matmul": true, | |
| "use_quantized_matmul_conv": false, | |
| "use_static_quantization": true, | |
| "use_stochastic_rounding": false, | |
| "use_svd": false, | |
| "weights_dtype": "uint4" | |
| }, | |
| "rope_scale": [ | |
| 1.0, | |
| 4.0, | |
| 4.0 | |
| ], | |
| "text_embed_dim": 1024, | |
| "use_crossattn_projection": false, | |
| "_name_or_path": null | |
| } | |