32 lines
969 B
Python
32 lines
969 B
Python
from argparse import ArgumentParser
|
|
|
|
from mastodon import Mastodon
|
|
from transformers import AutoTokenizer, AutoModelForCausalLM
|
|
|
|
|
|
parser = ArgumentParser()
|
|
parser.add_argument('-t', '--token', help='Mastodon application access token')
|
|
parser.add_argument('-i', '--input', default='i am',
|
|
help='initial input text for prediction')
|
|
parser.add_argument('-m', '--model', default='model',
|
|
help='path to load saved model')
|
|
args = parser.parse_args()
|
|
|
|
|
|
tokenizer = AutoTokenizer.from_pretrained('distilgpt2')
|
|
model = AutoModelForCausalLM.from_pretrained(args.model)
|
|
|
|
|
|
# Run the input through the model
|
|
inputs = tokenizer.encode(args.input, return_tensors="pt")
|
|
output = tokenizer.decode(model.generate(inputs, do_sample=True, max_length=25, top_p=0.9, temperature=0.8)[0])
|
|
print(output)
|
|
|
|
|
|
# Post it to Mastodon
|
|
mastodon = Mastodon(
|
|
access_token=args.token,
|
|
api_base_url='https://social.exozy.me/'
|
|
)
|
|
mastodon.status_post(output)
|