README.md

metadata

license: creativeml-openrail-m
language:
  - en
widget:
  - text: 1girl, fate
  - text: 1boy, league of legends
  - text: 1girl, genshin impact
  - text: 1boy, national basketball association
  - text: 1girl, spy x
  - text: 1girl, absurdres
tags:
  - stable-diffusion
  - anime
  - anything-v4
  - art
  - arxiv:2210.14140
datasets:
  - FredZhang7/anime-prompts-180K

Fast Anime PromptGen

Trained on the 80K Safebooru prompts

Todo:

• complete data preprocessing and training description
• upload Danbooru model

Text-to-image Examples

Prefix 1girl | Generated 1girl prompts | Model Anything V4

Prefix 1boy  | Generated 1boy prompts | Model Anything V4

Contrastive Search

pip install --upgrade transformers

import torch
from transformers import GPT2Tokenizer, GPT2LMHeadModel, pipeline
tokenizer = GPT2Tokenizer.from_pretrained('distilgpt2')
tokenizer.add_special_tokens({'pad_token': '[PAD]'})
model = GPT2LMHeadModel.from_pretrained('FredZhang7/anime-anything-promptgen')

prompt = r'1girl, genshin impact'

# generate text using fine-tuned model
nlp = pipeline('text-generation', model=model, tokenizer=tokenizer)

# generate 10 samples using greedy search
outs = nlp(prompt, max_length=76, num_return_sequences=10, do_sample=True, repetition_penalty=1.1, temperature=0.7, top_k=4, early_stopping=True)

print('\nInput:\n' + 100 * '-')
print('\033[96m' + prompt + '\033[0m')
print('\nOutput:\n' + 100 * '-')
for i in range(len(outs)):
    # remove trailing commas and double spaces
    outs[i] = str(outs[i]['generated_text']).replace('  ', '').rstrip(',')
print('\033[92m' + '\n\n'.join(outs) + '\033[0m\n')

Output Example:

Please see Fast GPT PromptGen for more info on the pipeline parameters.

Tips

• If you feel like a generated anime character doesn't show emotions, try emoticons like ;o, :o, ;p, :d, :p, and ;d in the prompt. I often use happy smirk, happy smile, laughing closed eyes, etc. to make the characters more lively and expressive.

• Adding absurdres, instead of highres and masterpiece, to a prompt tends to increase the sharpness of a generated image.