Update app.py

app.py

@@ -1,24 +1,39 @@
 
 import gradio as gr
 from transformers import AutoModelForCausalLM, AutoTokenizer
+from peft import PeftModel
 import torch
 
-model_name = "muhtasham/tajik-qwen2.5-7b_finetuned"
+base_model = "Qwen/Qwen2.5-7B"  # базовая модель
+adapter_model = "muhtasham/tajik-qwen2.5-7b_finetuned"  # таджикский fine-tune
 
-tokenizer = AutoTokenizer.from_pretrained(model_name)
-model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.float16, device_map="auto")
+tokenizer = AutoTokenizer.from_pretrained(base_model)
+
+# Загружаем базовую модель
+model = AutoModelForCausalLM.from_pretrained(
+    base_model,
+    torch_dtype="auto",
+    low_cpu_mem_usage=True,
+    device_map="cpu"
+)
+
+# Подключаем LoRA адаптер
+model = PeftModel.from_pretrained(model, adapter_model)
 
 def chat(prompt):
-    inputs = tokenizer(prompt, return_tensors="pt").to(model.device)
-    outputs = model.generate(**inputs, max_new_tokens=150, temperature=0.8, top_p=0.9)
-    return tokenizer.decode(outputs[0], skip_special_tokens=True)
+    try:
+        inputs = tokenizer(prompt, return_tensors="pt").to(model.device)
+        outputs = model.generate(**inputs, max_new_tokens=150, temperature=0.8, top_p=0.9)
+        return tokenizer.decode(outputs[0], skip_special_tokens=True)
+    except Exception as e:
+        return f"⚠️ Error: {str(e)}"
 
 demo = gr.Interface(
     fn=chat,
     inputs=gr.Textbox(lines=3, label="Введите запрос (на таджикском, русском или английском)"),
     outputs="text",
-    title="Tajik-Qwen2.5-7B Demo",
-    description="Нейросеть, обученная на таджикском языке — muhtasham/tajik-qwen2.5-7b_finetuned"
+    title="Tajik-Qwen2.5-7B Demo (LoRA)",
+    description="Файнтюнинг модели Qwen2.5-7B на таджикском языке."
 )
 
 if __name__ == "__main__":