--- license: other license_name: nvidia-open-model-license license_link: >- https://www.nvidia.com/en-us/agreements/enterprise-software/nvidia-open-model-license language: - en pipeline_tag: text-to-image tags: - comfyui - diffusion-single-file base_model: - nvidia/Cosmos-Predict2-14B-Text2Image base_model_relation: quantized --- For more information (including how to compress models yourself), check out https://huggingface.co/DFloat11 and https://github.com/LeanModels/DFloat11 Feel free to request for other models for compression as well, although models whose architecture I am unfamiliar with might be slightly tricky for me. ### How to Use #### ComfyUI Install my own fork of the DF11 ComfyUI custom node: https://github.com/mingyi456/ComfyUI-DFloat11-Extended. After installing the DF11 custom node, use the provided workflow [json](cosmos_predict2_14B_t2i-DF11-workflow.json), or simply replace the "Load Diffusion Model" node of an existing Kontext workflow with the "DFloat11 Model Loader" node. If you run into any issues, feel free to leave a comment. The workflow is also embedded in the below [png](cosmos_predict2_14B_t2i-DF11-workflow.png) image. ![](cosmos_predict2_14B_t2i-DF11-workflow.png) #### `diffusers` Refer to this [model](https://huggingface.co/mingyi456/Cosmos-Predict2-14B-Text2Image-DF11) instead. ### Compression Details This is the `pattern_dict` for compression: ```python pattern_dict_comfyui = { "t_embedder\.1": ( "linear_1", "linear_2", ), r"blocks\.\d+": ( "self_attn.q_proj", "self_attn.k_proj", "self_attn.v_proj", "self_attn.output_proj", "cross_attn.q_proj", "cross_attn.k_proj", "cross_attn.v_proj", "cross_attn.output_proj", "mlp.layer1", "mlp.layer2", "adaln_modulation_self_attn.1", "adaln_modulation_self_attn.2", "adaln_modulation_cross_attn.1", "adaln_modulation_cross_attn.2", "adaln_modulation_mlp.1", "adaln_modulation_mlp.2", ) } ```