Spaces:
Runtime error
Runtime error
File size: 1,354 Bytes
cb67dcf 53f76b1 3ab6ca9 cb67dcf 3ab6ca9 d84d90d 374cee2 cb67dcf 3ab6ca9 b0daf63 53f76b1 3ab6ca9 53f76b1 6dccfc2 ad2c8e4 cb67dcf 53f76b1 5b87039 53f76b1 5b87039 ad2c8e4 cb67dcf e80f947 cb67dcf 9d6a48d 2f1bde3 9d6a48d cb67dcf 761feb6 cb67dcf |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 |
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, token=access_token)
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,
eos_token_id=tokenizer.eos_token_id,
token=access_token
)
llm = HuggingFacePipeline(pipeline = pipeline, model_kwargs = {'temperature':0})
template = """Write a concise summary of the following:
"{text}"
CONCISE SUMMARY:"""
prompt = PromptTemplate(template=template, input_variables=["text"])
llm_chain = LLMChain(prompt=prompt, llm=llm)
text = text
return llm_chain.run(text)
with gr.Blocks() as demo:
text = gr.Textbox(label="Text")
summary = gr.Textbox(label="Summary")
greet_btn = gr.Button("Submit")
clear = gr.ClearnButton([text, summary])
greet_btn.click(fn=greet, inputs=text, outputs=summary, api_name="greet")
demo.launch() |