---
library_name: lucid
license: creativeml-openrail-m
tags:
  - base
  - Stable Diffusion
  - lucid
datasets:
  - LAION-5B
pipeline_tag: feature-extraction
---

# High-Resolution Image Synthesis with Latent Diffusion Models

> https://arxiv.org/abs/2112.10752

[Lucid](https://github.com/ChanLumerico/lucid) port of `https://huggingface.co/stable-diffusion-v1-5/stable-diffusion-v1-5`,
converted to Lucid-native safetensors.

## Available weights

| Tag | Params | GFLOPs | Size | Source |
|---|---|---|---|---|
| `CompVis_LAION` *(default)* | — | — | 3598.02 MB | https: |

## Usage

```python
import lucid
import lucid.models as models
from lucid.models.weights import Stable diffusionWeights

# default tag
model = models.stable_diffusion_v1(pretrained=True)

# explicit tag (enum or string)
model = models.stable_diffusion_v1(weights=Stable diffusionWeights.CompVis_LAION)
model = models.stable_diffusion_v1(pretrained="CompVis_LAION")

# feed token ids (tokenize with the matching lucid.utils.tokenizer)
input_ids = lucid.tensor([[101, 7592, 2088, 102]], dtype=lucid.int64)
out = model(input_ids)
hidden = out.last_hidden_state  # (B, T, hidden_size)
```

## Conversion

Converted from `https://huggingface.co/stable-diffusion-v1-5/stable-diffusion-v1-5` via
`python -m tools.convert_weights Stable Diffusion --tag CompVis_LAION`.
Key mapping + numerical parity verified against the source.

## License

`creativeml-openrail-m` — inherited from the original weights.

## Citation

```
@inproceedings{rombach2022high,
  title={High-Resolution Image Synthesis with Latent Diffusion Models},
  author={Rombach, Robin and Blattmann, Andreas and Lorenz, Dominik and Esser, Patrick and Ommer, Bj{\"o}rn},
  booktitle={CVPR},
  pages={10684--10695},
  year={2022}
}
```