| import streamlit as st | |
| from langchain_community.llms import CTransformers | |
| st.title("Generating Response with HuggingFace Models") | |
| st.markdown("## Model: `marella/gpt-2-ggml`") | |
| def get_response(question: str) -> str: | |
| """ | |
| This function takes a user input question and returns the response from the LLM model. | |
| Args: | |
| question (str): The user input question. | |
| Returns: | |
| str: The response from the LLM model. | |
| """ | |
| llm = CTransformers(model="marella/gpt-2-ggml") | |
| response = llm.invoke(question) | |
| return response | |
| user_input = st.text_area("Enter your query here...") | |
| if st.button("Get Response") and user_input: | |
| with st.spinner("Generating Response..."): | |
| answer = get_response(user_input) | |
| if answer is not None: | |
| st.success('Great! Response generated successfully') | |
| st.write(answer) |