# Model documentation & parameters

**Diffusion model**: Which model version to use. 

**Prompt**: The text prompt used, only applies to *conditional* diffusion image generators. These are `LDMTextToImageGenerator` and `StableDiffusionGenerator`. The other four models (`DDPMGenerator`, `DDPMGenerator`, `LDMGenerator` and `ScoreSdeGenerator`) are *unconditional*.



# Model card -- Image diffusion models

**Model Details**: Six diffusion models for image generation:
- `LDMTextToImageGenerator`
- `StableDiffusionGenerator`
- `DDPMGenerator`
- `DDPMGenerator`
- `LDMGenerator`
- `ScoreSdeGenerator`

For details, see the [Diffusers docs](https://huggingface.co/docs/diffusers/index)

**Developers**: Various developers of above models, wrapped by Diffusers developers into [`diffusers`](https://github.com/huggingface/diffusers)

**Distributors**: Diffusers code integrated into GT4SD.

**Model date**: 2022.

**Model version**: Diffusion models, checkpoints provided and distributed by [`diffusers`](https://github.com/huggingface/diffusers).

**Model type**: Various, see [`diffusers`](https://github.com/huggingface/diffusers) docs.

**Information about training algorithms, parameters, fairness constraints or other applied approaches, and features**: 
N.A.

**Paper or other resource for more information**: 
N.A.

**License**: MIT

**Where to send questions or comments about the model**: Open an issue on [`diffusers`](https://github.com/huggingface/diffusers) repo.

**Intended Use. Use cases that were envisioned during development**: Computer vision researchers experimenting with image generative models.

**Primary intended uses/users**: Computer vision researchers 

**Out-of-scope use cases**: Production-level inference, producing molecules with harmful properties.

**Metrics**: N.A.

**Datasets**: N.A.

**Ethical Considerations**: Unclear, please consult with original authors in case of questions.

**Caveats and Recommendations**: Unclear, please consult with original authors in case of questions.

Model card prototype inspired by [Mitchell et al. (2019)](https://dl.acm.org/doi/abs/10.1145/3287560.3287596?casa_token=XD4eHiE2cRUAAAAA:NL11gMa1hGPOUKTAbtXnbVQBDBbjxwcjGECF_i-WC_3g1aBgU1Hbz_f2b4kI_m1in-w__1ztGeHnwHs)

## Citation
```bib
@misc{von-platen-etal-2022-diffusers,
  author = {Patrick von Platen and Suraj Patil and Anton Lozhkov and Pedro Cuenca and Nathan Lambert and Kashif Rasul and Mishig Davaadorj and Thomas Wolf},
  title = {Diffusers: State-of-the-art diffusion models},
  year = {2022},
  publisher = {GitHub},
  journal = {GitHub repository},
  howpublished = {\url{https://github.com/huggingface/diffusers}}
}
```