File size: 2,688 Bytes
997984a fbaddc2 997984a fbaddc2 997984a fbaddc2 997984a fbaddc2 997984a fbaddc2 997984a fbaddc2 997984a fbaddc2 997984a fbaddc2 997984a fbaddc2 997984a fbaddc2 997984a fbaddc2 997984a fbaddc2 997984a fbaddc2 997984a fbaddc2 997984a |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 |
# 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
TBD, temporarily please cite:
```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}}
}
``` |