Update app.py

app.py

@@ -1,30 +1,12 @@
-import gradio as gr
-from transformers import AutoModelForCausalLM, AutoTokenizer
-import torch
-
-# Base modelとadapterの設定
-base_model_id = "unsloth/Llama-3.2-3B"  # または適切なbase model
-adapter_model_id = "MakiAi/Llama-3.2-3B-Instruct-bnb-4bit-OKU_wiki_llama3.1_8b_inst_Reflexive_chunk200_overlap700-10epochs"
 
-# モデルとトークナイザーの読み込み
-model = AutoModelForCausalLM.from_pretrained(
-    adapter_model_id,
-    torch_dtype=torch.float16,
-    device_map="auto"
-)
-tokenizer = AutoTokenizer.from_pretrained(adapter_model_id)
+import gradio as gr
+import spaces
+import transformers_gradio
 
-# Gradioインターフェースの作成
-def generate_text(prompt):
-    inputs = tokenizer(prompt, return_tensors="pt").to(model.device)
-    outputs = model.generate(**inputs, max_new_tokens=100)
-    return tokenizer.decode(outputs[0], skip_special_tokens=True)
+#demo = gr.load(name="MakiAi/Llama-3-2-3B-Instruct-bnb-4bit-OKU-v1-10epochs-adapter", src=transformers_gradio.registry)
+demo = gr.load(name="unsloth/Llama-3.2-1B", src=transformers_gradio.registry)
 
-demo = gr.Interface(
-    fn=generate_text,
-    inputs="text",
-    outputs="text"
-)
+demo.fn = spaces.GPU()(demo.fn)
 
 if __name__ == "__main__":
     demo.launch()