|
from transformers import pipeline |
|
import streamlit as st |
|
|
|
@st.cache_resource |
|
def context_text(text): return f"### Context\n{text}\n\n### Answer" |
|
|
|
@st.cache_resource |
|
def load_pipe(): |
|
return pipeline("token-classification", model="MSey/pbt_CaBERT_7_c10731") |
|
|
|
pipe = load_pipe() |
|
|
|
st.header("Test Environment for pbt_CaBERT_7_c10731") |
|
user_input = st.text_input("Enter your Prompt here:", "") |
|
contexted_ipnut = context_text(user_input) |
|
context_len = len(contexted_ipnut) |
|
|
|
if user_input: |
|
with st.spinner('Generating response...'): |
|
response = pipe(contexted_ipnut) |
|
st.write("Response:") |
|
st.text(response) |
|
|
