Fast Anime PromptGen

This model was trained on a dataset of 80,000 safe anime prompts for 3 epochs. I fetched the prompts from the Safebooru API endpoint, but only accepted unique prompts with up_score โ‰ฅ 8 and without any blacklisted tags. I didn't release the V1 model because it often generated gibberish prompts. After trying all means to correct that behavior, I eventually figured that the cause of the gibberish prompts is not from the pipeline params, model structure or training duration, but rather from the random usernames in the training data. Here's the complete prompt preprocessing algorithm.

Text-to-image Examples

Prefix 1girlโ€ƒ|โ€ƒGenerated 1girl promptsโ€ƒ|โ€ƒModel Anything V4

Prefix 1boyโ€ƒ |โ€ƒGenerated 1boy promptsโ€ƒ|โ€ƒModel 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-v2')

prompt = r'1girl, genshin'

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

# generate 10 samples using contrastive search
outs = nlp(prompt, max_length=76, num_return_sequences=10, do_sample=True, repetition_penalty=1.2, 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.

Awesome 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 also 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 can drastically increase the sharpness and resolution of a generated image.

Danbooru

Link to the Danbooru version

Downloads last month
2,283
Safetensors
Model size
88.2M params
Tensor type
F32
ยท
U8
ยท
Inference Examples
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social visibility and check back later, or deploy to Inference Endpoints (dedicated) instead.

Model tree for FredZhang7/anime-anything-promptgen-v2

Quantizations
1 model

Dataset used to train FredZhang7/anime-anything-promptgen-v2

Spaces using FredZhang7/anime-anything-promptgen-v2 3