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import torch | |
from transformers import pipeline | |
import gradio as gr | |
import spaces | |
from transformers import AutoTokenizer, AutoModelForCausalLM | |
def greet(name): | |
pipe = pipeline("text-generation", model="TinyLlama/TinyLlama-1.1B-Chat-v1.0", torch_dtype=torch.bfloat16, device_map="auto") | |
messages = [ | |
{ | |
"role": "system", | |
"content": "You are a friendly chatbot who always responds in the Professsional way", | |
}, | |
{"role": "user", "content": name}, | |
] | |
prompt = pipe.tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True) | |
outputs = pipe(prompt, max_new_tokens=2048, do_sample=True, temperature=0.7, top_k=50, top_p=0.95) | |
return outputs[0]["generated_text"] | |
demo = gr.Interface( | |
fn=greet, | |
inputs=["text"], | |
outputs=["text"], | |
) | |
demo.launch(share=True) |