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from llama_cpp.server.app import create_app, Settings | |
from fastapi.responses import HTMLResponse | |
import os | |
import requests | |
from llama_cpp import Llama | |
import gradio as gr | |
url="https://huggingface.co/TheBloke/WizardLM-13B-V1.2-GGUF/resolve/main/wizardlm-13b-v1.2.Q4_0.gguf" | |
response = requests.get(url) | |
with open("./model.gguf", mode="wb") as file: | |
file.write(response.content) | |
llm = Llama(model_path="./model.gguf") | |
def generate_text(input_text): | |
output = llm(f"Q: {input_text} A:", max_tokens=256, stop=["Q:", "\n"], echo=True) | |
return output['choices'][0]['text'] | |
input_text = gr.inputs.Textbox(lines= 10, label="Enter your input text") | |
output_text = gr.outputs.Textbox(label="Output text") | |
description = "llama.cpp implementation in python [https://github.com/abetlen/llama-cpp-python]" | |
examples = [ | |
["What is the capital of France? ", "The capital of France is Paris."], | |
["Who wrote the novel 'Pride and Prejudice'?", "The novel 'Pride and Prejudice' was written by Jane Austen."], | |
["What is the square root of 64?", "The square root of 64 is 8."] | |
] | |
gr.Interface(fn=generate_text, inputs=input_text, outputs=output_text, title="Llama Language Model", description=description, examples=examples).launch() | |