Pipeline Class: CraftlyImagePipeline; Transformer Diffusion Backbone: CraftlyImageTransformer2DModel (28 Layers, 48 Attention Heads, 64-channel Latent Input); Text Conditioning Backbone: CraftlyVisionModel (36 Layers, 2560 Hidden Dim); Latent Autoencoder: 16-channel Spatial VAE; Denoising Trajectory: Flow-Matching Euler Discrete Scheduler (Optimized 8-step Distillation).
Independent publisher
C
CraftlyrobotMushfiqur
Models in Library2
Datasets in Library0
Models on Hugging Face3
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Published tasks: Text to image.
Reported licenses: other. Open a record to review its specific license and conditions.
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Models
We are excited to open-source Qwen-Image-2.1, a unified text-to-image generation and image editing model in the Qwen family. With just 7B parameters in its visual generation component (32 Single-Stream DiT layers), Qwen-Image-2.1 balances generation quality, inference efficiency, and versatility. Four key improvements define this release: - Compact and Efficient — A lightweight architecture with mixed-granularity attention and prefix KV cache reuse delivers strong image quality at low computational cost. - Native Transparency, Unified Creation and Editing — Generate regular or transparent (RGBA) images from text, edit transparent layers, and extract subjects from photographs—all in one…