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ahmedfaiyaz/Mukh-Oboyob
Mukh-Oboyob is a text-to-image model from ahmedfaiyaz. Use it when you need an image from a text prompt. It is set up for diffusers.
Adapted from official Github repository: <a href="https://github.com/Codernob/Mukh-Oboyob"https://github.com/Codernob/Mukh-Oboyob</a Huggingface spaces: https://huggingface.co/spaces/gr33nr1ng3r/Mukh-Oboyob
Downloads · 30 days
44
2% of all-time downloads
All-time downloads
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.safetensors3.2 MB · 64%
From the Hugging Face model README
Adapted from official Github repository: <a href="https://github.com/Codernob/Mukh-Oboyob">https://github.com/Codernob/Mukh-Oboyob</a>
from diffusers import DiffusionPipeline
device="cuda"
pipeline = DiffusionPipeline.from_pretrained(
"CompVis/stable-diffusion-v1-4",
custom_pipeline="ahmedfaiyaz/Mukh-Oboyob"
)
pipeline.unet.load_attn_procs("gr33nr1ng3r/Mukh-Oboyob")
pipeline.to(device)
prompt = "মেয়েটির কালো চুল ছিল। মেয়েটির মুখে ভারী মেকাপ ছিল। মেয়েটির উঁচু গালের হাড় ছিল। মেয়েটির মুখ কিছুটা খোলা ছিল। মেয়েটির চেহারা ডিম্বাকৃতির। মেয়েটির চোখা নাক ছিল। মেয়েটির ঢেউ খেলানো চুল ছিল। মেয়েটির কানে দুল পরা ছিল। মেয়েটির লিপস্টিক পরা ছিল। "
image = pipeline(prompt, num_inference_steps=200, guidance_scale=7.5,height=128,width=128).images[0]
image
<Gallery />
Weights for this model are available in PyTorch format.
Download them in the Files & versions tab.
If you use any of the models or code,please cite the following paper:
@article{Saha2023,
title = {Mukh-Oboyob: Stable Diffusion and BanglaBERT enhanced Bangla Text-to-Face Synthesis},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2023.01411142},
url = {http://dx.doi.org/10.14569/IJACSA.2023.01411142},
year = {2023},
publisher = {The Science and Information Organization},
volume = {14},
number = {11},
author = {Aloke Kumar Saha and Noor Mairukh Khan Arnob and Nakiba Nuren Rahman and Maria Haque and Shah Murtaza Rashid Al Masud and Rashik Rahman}
}