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from transformers import (AutoModelForCausalLM,
AutoTokenizer,
GenerationConfig)
from peft import PeftModel
import gradio as gr
# Memuat model
base_model = AutoModelForCausalLM.from_pretrained(
"BioMistral/BioMistral-7B",
load_in_8bit=True,
device_map="auto"
)
model = PeftModel.from_pretrained(base_model, "sayyid14/BioMistralCancer5epoch")
generation_config = GenerationConfig(
do_sample=False,
num_beams=4,
repetition_penalty=1.15,
)
# Load tokenizer
tokenizer = AutoTokenizer.from_pretrained("BioMistral/BioMistral-7B", trust_remote_code=True)
tokenizer.pad_token = tokenizer.eos_token
# Fungsi respons
def chatbot_response(user_input):
PROMPT = f"""Below is a question about cancer. Please answer this question correctly. If you don't know the answer just say that you don't know and don't share false information.
### Question:
{user_input}
### Answer:"""
inputs = tokenizer(PROMPT, return_tensors="pt")
input_ids = inputs["input_ids"]
print("Generating...")
generation_output = model.generate(
input_ids=input_ids,
generation_config=generation_config,
return_dict_in_generate=True,
max_new_tokens=100,
pad_token_id=tokenizer.eos_token_id,
eos_token_id=tokenizer.eos_token_id
)
for s in generation_output.sequences:
result = tokenizer.decode(s).split("### Answer:")[1]
return result.strip()
# Membuat antarmuka
iface = gr.Interface(
fn=chatbot_response,
inputs=gr.Textbox(placeholder="Type your question...", label="User"),
outputs=gr.Textbox(label="Bot"),
title="BioMistralCancer",
description="Ask anything about Cancer",
css="""
body {
background-size: cover;
background-repeat: no-repeat;
background-position: center;
height: 100vh;
margin: 0;
}
.gradio-container {
background-color: rgba(255, 255, 255, 0.8);
border-radius: 10px;
padding: 20px;
backdrop-filter: blur(10px);
}
"""
)
# Menjalankan aplikasi
iface.launch(share=True)
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