|
Model trained on the TinyStories-Instruct Dataset, see https://arxiv.org/abs/2305.07759 |
|
|
|
------ EXAMPLE USAGE --- |
|
|
|
from transformers import AutoModelForCausalLM, AutoTokenizer, GenerationConfig |
|
|
|
model = AutoModelForCausalLM.from_pretrained('roneneldan/TinyStories-Instruct-33M') |
|
|
|
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) |