TinyStories-1M / README.md
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Model trained on the TinyStories Dataset, see https://arxiv.org/abs/2305.07759

------ EXAMPLE USAGE ---

from transformers import AutoModelForCausalLM, AutoTokenizer, GenerationConfig

model = AutoModelForCausalLM.from_pretrained('roneneldan/TinyStories-1M')

tokenizer = AutoTokenizer.from_pretrained("EleutherAI/gpt-neo-125M")

prompt = "Once upon a time there was"

input_ids = tokenizer.encode(prompt, return_tensors="pt")

Generate completion

output = model.generate(input_ids, max_length = 1000, num_beams=1)

Decode the completion

output_text = tokenizer.decode(output[0], skip_special_tokens=True)

Print the generated text

print(output_text)