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import gradio as gr | |
from transformers import AutoModelForCausalLM, AutoTokenizer | |
# Load the model and tokenizer | |
tokenizer = AutoTokenizer.from_pretrained("aisingapore/sea-lion-7b-instruct", trust_remote_code=True) | |
model = AutoModelForCausalLM.from_pretrained("aisingapore/sea-lion-7b-instruct", trust_remote_code=True) | |
def generate_response(prompt): | |
inputs = tokenizer(prompt, return_tensors="pt") | |
outputs = model.generate(**inputs) | |
return tokenizer.decode(outputs[0], skip_special_tokens=True) | |
iface = gr.Interface(fn=generate_response, inputs="text", outputs="text") | |
# Add a custom API route | |
def api_handler(data): | |
prompt = data['prompt'] | |
response = generate_response(prompt) | |
return {"response": response} | |
iface.api_routes = { | |
"/generate": {"POST": api_handler} | |
} | |
iface.launch(share=True, inline=True) | |