app.py

# import gradio as gr
# print("hello")
# gr.load("NousResearch/Yarn-Mistral-7b-128k",src="models").launch()
# from transformers import pipeline

# classifier = pipeline("sentiment-analysis")
# def get_class(input):
#     return classifier("I've been waiting for a HuggingFace course my whole life.")

# iface = gr.Interface(fn=get_class, inputs="text", outputs=['text'], title='hello', description='play around')
# iface.launch()
fsddsf

# Use a pipeline as a high-level helper
from transformers import pipeline

my_pipe = pipeline("text-generation", model="NousResearch/Yarn-Mistral-7b-128k")

def get_class_1(input):
    return my_pipe(input)

iface = gr.Interface(fn=get_class_1, inputs="text", outputs=['text'], title='hello', description='LLM')
iface.launch()