Model reference · open weights

LCM_Dreamshaper

LCM_Dreamshaper is an open-weight image model from SimianLuo, listed in the AxForge catalogue. AxForge can bring it up on EU-owned hardware for you on request — with the licence handled where one is required.

Image SimianLuo 1 variants 114k downloads/mo
Request this model on EU hardware All served models Not on the shared API today — deployed on request.

About

What LCM_Dreamshaper is

Latent Consistency Models Official Repository of the paper: Latent Consistency Models. Project Page: https://latent-consistency-models.github.io Try our Hugging Face demos: [](https://huggingface.co/spaces/SimianLuo/LatentConsistencyModel) Model Descriptions: Distilled from Dreamshaper v7 fine-tune of Stable-Diffusion v1-5 with only 4,000 training iterations (~32 A100 GPU Hours). Generation Results: 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 scale w=8, batchsize=4, using a A800 GPU. Usage You can try out Latency Consistency Models directly on: [](https://huggingface.co/spaces/SimianLuo/LatentConsistencyModel) To run the model yourself, you can leverage the 🧨 Diffusers library: 1. Install the library: 2. Run the model: For more information, please have a look at the official docs: 👉 https://huggingface.co/docs/diffusers/api/pipelines/latentconsistencymodels#latent-consistency-models Usage (Deprecated) 1. Install the library: 2. Run the model: BibTeX

Summarised from the published model card. Read the full card on the HuggingFace links below.

Specifications

What it is

MakerSimianLuo
TypeImage models
Parameters (lead)860M
Variants1
Runs withdiffusers
Released2023-10-14
Popularity114k downloads / month
Likes416
LicenceOpen weights

How it works

How image models work

Text promptwhat to makeText encoderunderstands itDiffusion stepsdenoise to pixelsImagePNG / JPEGA diffusion model starts from noise and denoises it, guided by your prompt, into a finished image.

Variants

Sizes & precisions

Open weights ship in several sizes and precisions. One page, all the variants — pick the one that fits your GPU. VRAM figures are estimates from model size.

VariantParamsPrecisionVRAMFits 16 GBWeights
LCM_Dreamshaper_v7860MBF16~2 GBWeights ↗

Using it via the API

Call it like any OpenAI endpoint

Once AxForge deploys lcm-dreamshaper for you, it answers on the OpenAI-compatible API — the same base URL and keys as every other model. (lcm-dreamshaper below is illustrative; you get the exact model name on deployment.)

$ curl -sS https://api.axforge.ai/v1/images/generations \
  -H "Authorization: Bearer $AXFORGE_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"model":"lcm-dreamshaper","prompt":"a red bicycle","size":"1024x1024"}'

Details

Languages, data & research

Languages

en

Tags

diffusers onnx safetensors text-to-image en diffusers:LatentConsistencyModelPipeline

Papers

Licence

Open weights

Open weights under mit — commercial use is permitted. Deploy it on AxForge EU hardware on request. Read the licence ↗

Sources

Weights & code

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