76 lines
2.1 KiB
Python
76 lines
2.1 KiB
Python
from argparse import ArgumentParser
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from random import randint, choice
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from mastodon import Mastodon
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from transformers import AutoTokenizer, AutoModelForCausalLM
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parser = ArgumentParser()
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parser.add_argument('-i', '--instance', help='Mastodon instance hosting the bot')
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parser.add_argument('-t', '--token', help='Mastodon application access token')
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parser.add_argument('-n', '--input', help='initial input text')
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parser.add_argument('-d', '--data', default='data',
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help='data for automatic input generation')
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parser.add_argument('-m', '--model', default='model',
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help='path to load saved model')
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args = parser.parse_args()
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tokenizer = AutoTokenizer.from_pretrained('distilgpt2')
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model = AutoModelForCausalLM.from_pretrained(args.model)
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if args.input is None:
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# Create random input
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if randint(0, 1) == 0:
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args.input = choice([
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'I am',
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'My life is',
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'Computers are',
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'This is',
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'My',
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'I\'ve',
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'No one',
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'I love',
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'I will die of',
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'I',
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'The',
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'Anime',
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'I\'m going to die',
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'Hello',
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'@ta180m@exozy.me',
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'Life',
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'My favorite',
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'I\'m not',
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'I hate',
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'I think',
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'In my opinion',
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'Breaking news:',
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'Have I ever told you that',
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'I read on the news that',
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'I never knew that'
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])
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else:
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with open(args.data, 'r') as f:
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line = choice(f.readlines()).split()
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args.input = line[0] + ' ' + line[1]
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# Run the input through the model
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print(args.input)
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inputs = tokenizer.encode(args.input, return_tensors="pt")
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output = tokenizer.decode(model.generate(
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inputs, do_sample=True, max_length=150, top_p=0.9)[0])
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print(output)
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# Post it to Mastodon
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mastodon = Mastodon(
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access_token=args.token,
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api_base_url=args.instance
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)
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post = output.split('\n')[0]
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if len(post) < 200:
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post = output.split('\n')[0] + '\n' + output.split('\n')[1]
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mastodon.status_post(post[:500])
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