Spaces:
Runtime error
Runtime error
import gradio as gr | |
import torch | |
import transformers | |
from transformers import AutoTokenizer | |
from langchain import LLMChain, HuggingFacePipeline, PromptTemplate | |
import os | |
access_token = os.getenv("Llama2") | |
def greet(text): | |
model = "meta-llama/Llama-2-7b-chat-hf" | |
tokenizer = AutoTokenizer.from_pretrained(model) | |
pipeline = transformers.pipeline( | |
"text-generation", | |
model=model, | |
tokenizer=tokenizer, | |
torch_dtype=torch.bfloat16, | |
trust_remote_code=True, | |
device_map="auto", | |
max_length=1000, | |
do_sample=True, | |
top_k=10, | |
num_return_sequences=1, | |
pad_token_id=tokenizer.eos_token_id | |
) | |
llm = HuggingFacePipeline(pipeline = pipeline, model_kwargs = {'temperature':0}) | |
template = """ | |
Write a summary of the following text delimited by triple backticks. | |
Return your response which covers the key points of the text. | |
```{text}``` | |
SUMMARY: | |
""" | |
prompt = PromptTemplate(template=template, input_variables=["text"]) | |
llm_chain = LLMChain(prompt=prompt, llm=llm) | |
summary = llm_chain.run(text) | |
return summary | |
with gr.Blocks() as demo: | |
text = gr.Textbox(label="Text") | |
summary = gr.Textbox(label="Summary") | |
greet_btn = gr.Button("Submit") | |
greet_btn.click(fn=greet, inputs=text, outputs=summary, api_name="greet") | |
demo.launch() |