Create app.py

app.py

@@ -0,0 +1,39 @@
+import gradio as gr
+import torch
+from transformers import AutoModelForCausalLM, AutoTokenizer
+
+def run_LLM (model, tokenizer, streamer, prompt):
+
+    token_ids = tokenizer.encode(prompt, return_tensors="pt")
+    output_ids = model.generate(
+        input_ids=token_ids.to(model.device),
+        #max_new_tokens=300,
+        max_new_tokens=3000000,
+        do_sample=True,
+        temperature=0.8,
+    )
+
+    n_tokens = len(output_ids[0])
+    output_text = tokenizer.decode(output_ids[0])
+
+    return (output_text, n_tokens)
+
+def display_message():
+    model = AutoModelForCausalLM.from_pretrained("cyberagent/calm2-7b-chat",
+                                                 device_map="cuda",
+                                                 torch_dtype="auto")
+    tokenizer = AutoTokenizer.from_pretrained("cyberagent/calm2-7b-chat")
+    streamer = TextStreamer(tokenizer, skip_prompt=True, skip_special_tokens=True)
+
+    prompt = """わが国の経済について今後の予想を教えてください。
+    ASSISTANT: """
+
+    (result, n_tokens) = run_LLM(model, tokenizer, streamer, prompt)
+
+    return result
+
+
+if __name__ == '__main__':
+
+    iface = gr.Interface(fn=display_message, inputs=None, outputs="text")
+    iface.launch()