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# app.py (Versi CPU - Lambat)
import torch
import gradio as gr
from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline
# --- KONFIGURASI ---
ADAPTER_MODEL_ID = "DeryFerd/qwen2-0.5b-taksonomi-finetune"
BASE_MODEL_ID = "Qwen/Qwen2-0.5B-Instruct"
# --- Muat Model & Tokenizer untuk CPU ---
print("Loading base model onto CPU...")
# Perubahan 1: Memuat model tanpa optimasi 4-bit dan dengan tipe data standar
base_model = AutoModelForCausalLM.from_pretrained(
BASE_MODEL_ID,
torch_dtype=torch.float32, # Tipe data standar untuk CPU
device_map="cpu", # Perubahan 2: Paksa model untuk berjalan di CPU
)
print("Loading tokenizer...")
tokenizer = AutoTokenizer.from_pretrained(BASE_MODEL_ID)
# Perubahan 3: Muat adapter LoRA dengan cara standar dari PEFT
from peft import PeftModel
print("Loading LoRA adapter...")
model = PeftModel.from_pretrained(base_model, ADAPTER_MODEL_ID)
print("Model ready on CPU!")
# --- Buat Pipeline untuk Inferensi di CPU ---
# Perubahan 4: Menggunakan pipeline transformers standar yang lebih stabil
pipe = pipeline(
"text-generation",
model=model,
tokenizer=tokenizer,
device=-1, # -1 berarti menggunakan CPU
)
# --- Fungsi untuk Inferensi ---
def get_taxonomy(scientific_name):
# Template prompt yang sama
alpaca_prompt = """Below is an instruction that describes a task. Write a response that appropriately completes the request.
### Instruction:
Provide the complete taxonomy for the given scientific name.
### Input:
{}
### Response:
{}"""
prompt = alpaca_prompt.format(scientific_name, "")
# Menjalankan pipeline
outputs = pipe(prompt, max_new_tokens=128, do_sample=False)
# Membersihkan output
generated_text = outputs[0]['generated_text']
try:
response_only = generated_text.split("### Response:")[1].strip()
except IndexError:
response_only = "Model tidak menghasilkan respons yang valid."
return response_only
# --- Buat UI dengan Gradio ---
iface = gr.Interface(
fn=get_taxonomy,
inputs=gr.Textbox(lines=2, label="Scientific Name", placeholder="Contoh: Orycteropus afer"),
outputs=gr.Textbox(lines=5, label="Taksonomi Hasil Prediksi Model"),
title="Animal Taxonomy AI (CPU Version)",
description="Demo fine-tuning LLM yang berjalan di CPU. Harap bersabar, respons akan lebih lambat.",
allow_flagging="never"
)
iface.launch() |