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from transformers import AutoTokenizer | |
import transformers | |
import torch | |
import gradio as gr | |
model= "PY007/TinyLlama-1.1B-step-50K-105b" | |
tokenizer = AutoTokenizer.from_pretrained(model) | |
pipeline = transformers.pipeline( | |
"text-generation", | |
model=model, | |
torch_dtype=torch.float16, | |
device_map="auto", | |
) | |
sequences = pipeline( | |
'The TinyLlama project aims to pretrain a 1.1B Llama model on 3 trillion tokens. With some proper optimization, we can achieve this within a span of "just" 90 days using 16 A100-40G GPUs ππ. The training has started on 2023-09-01.Chat Using TinyLlama', | |
do_sample=True, | |
top_k=10, | |
num_return_sequences=1, | |
repetition_penalty=1.5, | |
eos_token_id=tokenizer.eos_token_id, | |
max_length=500, | |
) | |
for seq in sequences: | |
print(f"Result :{seq['generated_text']}") |