bevelapi / models /tinystories.py
BeveledCube's picture
Added EOS toke stuff increased new token limit and added QOL features to frontent
8e724ea
from transformers import AutoTokenizer, AutoModelForCausalLM
model_name = "roneneldan/TinyStories-1M"
def load():
global model
global tokenizer
model = AutoModelForCausalLM.from_pretrained(model_name)
tokenizer = AutoTokenizer.from_pretrained(model_name)
def generate(input_text):
input_ids = tokenizer.encode(input_text, return_tensors="pt")
output_ids = model.generate(
input_ids,
no_repeat_ngram_size=2,
max_new_tokens=200,
eos_token_id=tokenizer.eos_token_id,
temperature=0.2
)
return tokenizer.decode(output_ids[0], skip_special_tokens=True)