`qwen3.5_9b_qwen_image_2.1_pe` 모델은 프롬프트 향상을 위한 것으로, `Generate Text` 노드와 함께 사용됩니다. 더 빠른 추론을 위해 전체 Turbo 모델 또는 기본 모델에서 추출한 Turbo LoRA를 사용하십시오. 8단계와 cfg 1을 사용하세요. Qwen Image 2.1: 이미지 편집 전후 Qwen Image 2.1: 텍스트에서 이미지 생성 Qwen Image 2.1 Turbo: 이미지 편집 전후 Qwen Image 2.1 Turbo: 텍스트에서 이미지 생성 배경 제거: Qwen Image 2.1 전후
- https://huggingface.co/dx8152/Qwen-Edit-2509-Light-Migration/ - https://huggingface.co/dx8152/Qwen-Edit-2509-Multiple-angles - https://huggingface.co/dx8152/Qwen-Image-Edit-2509-Fusion - https://huggingface.co/dx8152/Qwen-Image-Edit-2509-Relight - https://huggingface.co/lrzjason/QwenEdit-Anything2Real_Alpha/ --- - Qwen-Image-Edit-2509-Light-Migration.safetensors from dx8152/Qwen-Edit-2509-Light-Migration - Qwen-Edit-2509-Multiple-angles.safetensors from dx8152/Qwen-Edit-2509-Multiple-angles - Qwen-Image-Edit-2509-Relight.safetensors from dx8152/Qwen-Image-Edit-2509-Fusion - Qwen-Image-Edit-2509-Relight.safetensors fromt dx8152/Qwen-Image-Edit-2509-Relight - Qwen-Image-Edit-2509-Anything2RealAlpha.safetensors from lrzjason/QwenEdit-Anything2Real_Alpha Qwen Image Edit 2509 Before After Qwen Image Edit 2511 Int8: Image Edit Before After Qwen Image Edit 2511 - Material Replacement Before After Qwen Image Edit Before After Image Relight Before After Image Inflation Effect with INFL8 LoRA Before After
- https://huggingface.co/ByteDance-Seed/SeedVR2-3B - https://huggingface.co/ByteDance-Seed/SeedVR2-7B Converted with `seedvr2_convert.py` from Comfy-Org/comfy-model-tools. Video Upscale: SeedVR2 3B Int8 Before After Image Upscale: SeedVR2 7B Int8 Before After Image Upscale: SeedVR2 3B Int8 Before After
This is an archival re-upload of Stable Diffusion v1.5, originally at https://huggingface.co/runwayml/stable-diffusion-v1-5 until RunwayML took down that page. This model is from 2022, and is several major generational upgrades behind, it is being preserved here for technical & accessibility reasons (eg legacy model testing). https://huggingface.co/Comfy-Org/stable-diffusion-v1-5-archive/blob/main/v1-5-pruned-emaonly.safetensors is the exact original hash-identical model as uploaded by RunwayML.
This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the common_voice 8.0 dataset as well as other datasets listed below. It achieves the following results on the evaluation set: - Loss: 0.1271 - Wer: 0.1475 - Cer: 0.0329 The `eval.py` script results using a LM are: - WER: 0.07274312090176113 - CER: 0.021207369275558875
This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the common_voice 8.0 dataset. It achieves the following results on the evaluation set: - learning_rate: 7e-4 - train_batch_size: 32 - eval_batch_size: 8 - seed: 42 - gradient_accumulation_steps: 20 - total_train_batch_size: 640 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - lr_scheduler_warmup_steps: 500 - num_epochs: 50 - mixed_precision_training: Native AMP - Transformers 4.16.0.dev0 - Pytorch 1.10.1+cu102 - Datasets 1.17.1.dev0 - Tokenizers 0.11.0
Run a 177B parameter model on a consumer PC by **streaming it from an NVMe SSD**. This GGUF is made for SSD offloading: about 100 GiB of the 119 GiB file stays on the SSD and is read as needed, so the model runs on a 16 GB GPU with 32 GB of RAM. It runs with inferredThoughts, an open-source engine for SSD streaming of mixture-of-experts models. RTX 5060 Ti 16 GB, 32 GB DDR5 RAM, Gen5 NVMe SSD, native Windows 11, `inferred serve ` version 1.1, default settings. Requirements: - An RTX 50-series or RTX PRO Blackwell GPU (16 GB VRAM), NVIDIA driver R570+, CUDA 12.8+ - 32 GB of RAM and a fast local NVMe SSD (Gen4 or Gen5) with 128 GB free - Windows 11 or WSL2 (Ubuntu 24.04)