--- license: apache-2.0 base_model: - nvidia/ChronoEdit-14B-Diffusers base_model_relation: quantized library_name: diffusers tags: - sdnq - 4-bit - chrono --- 4 bit (UINT4 with SVD rank 32) quantization of [nvidia/ChronoEdit-14B-Diffusers](https://huggingface.co/nvidia/ChronoEdit-14B-Diffusers) using [SDNQ](https://github.com/vladmandic/sdnext/wiki/SDNQ-Quantization). Usage: ``` pip install git+https://github.com/Disty0/sdnq ``` ```py import math import torch from PIL import Image from diffusers.utils import load_image from chronoedit_diffusers.pipeline_chronoedit import ChronoEditPipeline from sdnq import SDNQConfig # import sdnq to register it into diffusers and transformers pipe = ChronoEditPipeline.from_pretrained("Disty0/ChronoEdit-14B-SDNQ-uint4-svd-r32", torch_dtype=torch.bfloat16) pipe.enable_model_cpu_offload() input_image = load_image("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/cat.png") max_area = 480 * 832 aspect_ratio = input_image.height / input_image.width mod_value = pipe.vae_scale_factor_spatial * pipe.transformer.config.patch_size[1] height = round(math.sqrt(max_area * aspect_ratio)) // mod_value * mod_value width = round(math.sqrt(max_area / aspect_ratio)) // mod_value * mod_value input_image = input_image.resize((width, height)) output = pipe( image=input_image, prompt="Add a hat to the cat", height=height, width=width, num_frames=5, guidance_scale=2.5, generator=torch.manual_seed(0), ).frames[0] image = Image.fromarray((output[-1] * 255).clip(0, 255).astype("uint8")) image.save("chrono-edit-sdnq-uint4-svd-r32.png.png") ``` Original BF16 vs SDNQ quantization comparison: | Quantization | Model Size | Visualization | | --- | --- | --- | | Input Image | - | ![Input Image](https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/cat.png) | | Original BF16 | 28.6 GB | ![Original BF16](https://cdn-uploads.huggingface.co/production/uploads/6456af6195082f722d178522/2Wbgz_tMCTuyKlsltQTWS.png) | | SDNQ UINT4 | 9.5 GB | ![SDNQ UINT4](https://cdn-uploads.huggingface.co/production/uploads/6456af6195082f722d178522/xKgH4nGwP-H5mtxYS5qqS.png) |