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https://colab.research.google.com/drive/1Dlm8FA9JjjcqJIkfCagaIQWex8Ho5IKI#scrollTo=e8xIjRNsl3Bb
from transformers import AutoTokenizer, AutoModelForCausalLM
tokenizer = AutoTokenizer.from_pretrained("GeneralRincewind/ShakespeareGPT")
model = AutoModelForCausalLM.from_pretrained("GeneralRincewind/ShakespeareGPT")
#### Generate text
from transformers import TextStreamer
tokenized_text = tokenizer("", return_tensors="pt", truncation=True)
input_ids = tokenized_text.input_ids
streamer = TextStreamer(tokenizer)
model.eval()
full_completion = model.generate(inputs=tokenized_text["input_ids"].to("cuda"),
attention_mask=tokenized_text["attention_mask"].to("cuda"),
temperature=0.9,
top_k=80,
top_p=0.65,
do_sample=True,
streamer=streamer,
num_beams=1,
max_new_tokens=500,
eos_token_id=tokenizer.eos_token_id,
pad_token_id=tokenizer.pad_token_id,
repetition_penalty=1)
decoded_text = tokenizer.decode(full_completion[0])
print(decoded_text)
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