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import gradio as gr
from transformers import AutoTokenizer
import spaces
# Function to load and tokenize the message using the selected tokenizer
@spaces.GPU
def tokenize(message, tokenizer_name):
try:
tokenizer = AutoTokenizer.from_pretrained(tokenizer_name)
return str(tokenizer.encode(message))
except Exception as e:
return f"Error loading tokenizer: {str(e)}"
# Wrapper function to handle chat interaction
def chat(message, history, tokenizer_name):
tokenized_message = tokenize(message, tokenizer_name)
history.append((message, tokenized_message))
return history, history
# Gradio interface
with gr.Blocks() as demo:
tokenizer_input = gr.Textbox(placeholder="Enter the tokenizer name (e.g., gpt2, bert-base-uncased)", label="Tokenizer Name")
chatbot = gr.Chatbot()
msg = gr.Textbox()
clear = gr.Button("Clear")
def clear_history():
return [], []
msg.submit(chat, inputs=[msg, chatbot, tokenizer_input], outputs=[chatbot, chatbot])
clear.click(clear_history, outputs=[chatbot, chatbot])
demo.launch()
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