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Portuguese image generation
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from diffusers import StableDiffusionPipeline | |
from transformers import AutoTokenizer, AutoModelForSeq2SeqLM | |
from torch import autocast | |
PT_PROMPT = "Um gato com um chapéu, pintura a aguarelas" # A cat with a hat, watercolor painting | |
# translation PT -> EN | |
transl_model_id = "Narrativa/mbart-large-50-finetuned-opus-pt-en-translation" | |
tokenizer = AutoTokenizer.from_pretrained(transl_model_id) | |
text_model = AutoModelForSeq2SeqLM.from_pretrained(transl_model_id) | |
pt_tokens = tokenizer([PT_PROMPT], return_tensors="pt") | |
en_tokens = text_model.generate(**pt_tokens, max_new_tokens=100, num_beams=8, early_stopping=True) | |
en_prompt = tokenizer.batch_decode(en_tokens, skip_special_tokens=True) | |
print(f"translation: [PT] {PT_PROMPT} -> [EN] {en_prompt[0]}") | |
# text -> image | |
# remember: you need to request access to stable diffusion. See the colab below for more information | |
# https://colab.research.google.com/github/huggingface/notebooks/blob/main/diffusers/stable_diffusion.ipynb | |
diffusion_model_id = "CompVis/stable-diffusion-v1-3-diffusers" | |
pipe = StableDiffusionPipeline.from_pretrained(diffusion_model_id, use_auth_token=True) | |
with autocast("cuda"): | |
image = pipe(en_prompt, guidance_scale=7.5, height=512, width=512)["sample"][0] | |
image.save(f"stable_ai_img.png") |
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