Text-to-Image
Diffusers
Safetensors
Cosmos
sdnq
transformer-component
anima
uint4
4bit
8-bit precision
Instructions to use WaveCut/Anima-Preview-3-SDNQ-uint4 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 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", 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 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 Settings
- Draw Things
- DiffusionBee
Add SDNQ uint4 quantized Anima transformer
Browse files
README.md
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---
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license: other
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base_model: circlestone-labs/Anima
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tags:
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- sdnq
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- uint4
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- 4bit
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- diffusion-single-file
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- text-to-image
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- cosmos
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---
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# Anima SDNQ UINT4 Diffusers Transformer
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SDNQ 4-bit (`uint4`) quantization of the `circlestone-labs/Anima` Preview3 diffusion transformer checkpoint.
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Important: the upstream Anima checkpoint contains additional `llm_adapter.*` weights used by the native ComfyUI loader. Current `diffusers.CosmosTransformer3DModel.from_single_file` ignores those adapter weights, so this repo is a diffusers-compatible SDNQ transformer artifact, not a full ComfyUI-native split checkpoint replacement.
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config.json
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{
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"_class_name": "CosmosTransformer3DModel",
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"_diffusers_version": "0.38.0",
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"adaln_lora_dim": 256,
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"attention_head_dim": 128,
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"concat_padding_mask": true,
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"controlnet_block_every_n": null,
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"crossattn_proj_in_channels": 1024,
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"encoder_hidden_states_channels": 1024,
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"extra_pos_embed_type": null,
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"img_context_dim_in": null,
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"img_context_dim_out": 2048,
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"img_context_num_tokens": 256,
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"in_channels": 16,
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"max_size": [
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128,
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240,
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240
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],
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"mlp_ratio": 4.0,
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"num_attention_heads": 16,
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"num_layers": 28,
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"out_channels": 16,
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"patch_size": [
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1,
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2,
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2
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],
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"quantization_config": {
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"add_skip_keys": false,
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"dequantize_fp32": false,
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"dynamic_loss_threshold": null,
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"group_size": 0,
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"is_integer": true,
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"is_training": false,
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"modules_dtype_dict": {},
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"modules_quant_config": {},
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"modules_to_not_convert": [
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"crossattn_proj",
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"patch_embed",
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"transformer_blocks.0.norm*",
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"norm_out",
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"proj_out",
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"learnable_pos_embed",
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"time_embed"
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],
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"non_blocking": false,
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"quant_conv": false,
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"quant_embedding": false,
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"quant_method": "sdnq",
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"quantization_device": null,
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"quantized_matmul_dtype": null,
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"return_device": null,
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"sdnq_version": "0.1.8",
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"svd_rank": 32,
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"svd_steps": 8,
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"use_dynamic_quantization": false,
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"use_grad_ckpt": true,
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"use_quantized_matmul": true,
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"use_quantized_matmul_conv": false,
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"use_static_quantization": true,
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"use_stochastic_rounding": false,
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"use_svd": false,
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"weights_dtype": "uint4"
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},
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"rope_scale": [
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1.0,
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4.0,
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4.0
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],
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"text_embed_dim": 1024,
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"use_crossattn_projection": false
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}
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diffusion_pytorch_model-00001-of-00003.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:17539390f73da7346934e68e0dc48c01e49eef1fa61c3d0b324bcb45a7ba37e4
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size 499618232
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diffusion_pytorch_model-00002-of-00003.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:e4b10de93317e2bd7cd8ad0d1efb8bd264eecabad604d818bc45e9704230dc87
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size 497771600
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diffusion_pytorch_model-00003-of-00003.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:7ff2e0a2a931e2932e015bf492082470abcb5363f5745acd195195ac0f04d656
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size 139089360
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diffusion_pytorch_model.safetensors.index.json
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The diff for this file is too large to render.
See raw diff
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quantization_config.json
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{
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"add_skip_keys": false,
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"dequantize_fp32": false,
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"dynamic_loss_threshold": null,
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"group_size": 0,
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"is_integer": true,
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"is_training": false,
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"modules_dtype_dict": {},
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"modules_quant_config": {},
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"modules_to_not_convert": [],
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"non_blocking": false,
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"quant_conv": false,
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"quant_embedding": false,
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"quant_method": "sdnq",
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"quantization_device": null,
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"quantized_matmul_dtype": null,
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"return_device": null,
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"sdnq_version": "0.1.8",
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"svd_rank": 32,
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"svd_steps": 8,
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"use_dynamic_quantization": false,
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"use_grad_ckpt": true,
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"use_quantized_matmul": true,
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"use_quantized_matmul_conv": false,
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"use_static_quantization": true,
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"use_stochastic_rounding": false,
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"use_svd": false,
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"weights_dtype": "uint4"
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}
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