SimianLuo/LCM_Dreamshaper_v7
text-to-image model by SimianLuo
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Model card & documentation
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Official Repository of the paper: Latent Consistency Models. Project Page: https://latent-consistency-models.github.io [](https://huggingface.co/spaces/SimianLuo/LatentConsistencyModel) Distilled from Dreamshaper v7 fine-tune of Stable-Diffusion v1-5 with only 4,000 training iterations (32 A100 GPU Hours). By distilling classifier-free guidance into the model's input, LCM can generate high-quality images in very short inference time. We compare the inference time at the setting of 768 x 768 resolution, CFG…
Read the full model card ↗ · Preview checked 2026-10-27T16:32:30.448Z
Inside the original model card — Document outline
- Latent Consistency Models
- Try our Hugging Face demos:
- Model Descriptions:
- Generation Results:
- Usage
- Usage (Deprecated)
- BibTeX
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Model overview
SimianLuo/LCM_Dreamshaper_v7 is a text-to-image model repository published by SimianLuo on Hugging Face. The source reports the diffusers library.
This page summarizes Hub metadata. For intended use, training data, evaluation results and limitations, consult the original model card.
Model facts
- Task
- text-to-image
- Library
- diffusers
- Recent downloads (30 days)
- 162,938
- Cumulative likes
- 417
- Hugging Face trending score
- 0
- Reported safetensors parameters
- 859,602,884
- Architecture
- Not reported
- License
- mit
- Access
- Not gated by Hugging Face
- Created
- 2023-10-14T08:26:52.000Z
- Last modified
- 2024-03-05T08:32:22.000Z
Compatibility and lineage
Reported languages: en
Base-model lineage was not included.
Parameter count is not a RAM/VRAM requirement. Check precision, quantization, context length and runtime compatibility in the model card; no hardware or API-cost claim is inferred here.
Use and evaluate
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Source and freshness
Source: Hugging Face Hub. Metadata observed 2026-11-01T06:51:31.475Z. Daily imports are snapshots, not real-time monitoring.
Popularity and source listings do not establish security, suitability, licensing rights or benchmark performance.
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