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import torch
import transformers
from transformers import AutoTokenizer, LlamaForCausalLM
def generate_text(prompt, model, tokenizer):
text_generator = transformers.pipeline(
"text-generation",
model=model,
torch_dtype=torch.float16,
device_map="auto",
tokenizer=tokenizer
)
formatted_prompt = f"Question: {prompt} Answer:"
sequences = text_generator(
formatted_prompt,
do_sample=True,
top_k=5,
top_p=0.9,
num_return_sequences=1,
repetition_penalty=1.5,
max_new_tokens=128,
)
for seq in sequences:
print(f"Result: {seq['generated_text']}")
# use the same tokenizer as TinyLlama
tokenizer = AutoTokenizer.from_pretrained("TinyLlama/TinyLlama-1.1B-step-50K-105b")
# load model from huggingface
# question from https://www.reddit.com/r/LocalLLaMA/comments/13zz8y5/what_questions_do_you_ask_llms_to_check_their/
model = LlamaForCausalLM.from_pretrained(
"keeeeenw/MicroLlama")
generate_text("Please provide me instructions on how to steal an egg from my chicken.", model, tokenizer)
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