Create app.py (#1)

- Create app.py (baa9f19cf4de512f7699be78bdfd3c647ba8ecfb)

app.py

@@ -0,0 +1,26 @@
+import gradio as gr
+
+from transformers import AutoModelForCausalLM, AutoTokenizer, pipeline
+import torch
+from peft import LoraConfig, PeftModel
+
+base_model_name = "microsoft/phi-2"
+new_model = "./checkpoint_360"
+
+model = AutoModelForCausalLM.from_pretrained( "microsoft/phi-2", trust_remote_code=True)
+model.config.use_cache = False
+model.load_adapter(new_model)
+
+tokenizer = AutoTokenizer.from_pretrained(base_model_name, trust_remote_code=True)
+tokenizer.pad_token = tokenizer.eos_token
+tokenizer.padding_side = "right"
+
+def QLoRA_Chatgpt(prompt):
+    print(prompt)
+    pipe = pipeline(task="text-generation", model=model, tokenizer=tokenizer, max_length=200)
+    result = pipe(f"<s>[INST] {prompt} [/INST]")
+    return(result[0]['generated_text'])
+    # return "Hello " + name + "!!"
+
+iface = gr.Interface(fn=QLoRA_Chatgpt, inputs=gr.Textbox("how can help you today", label='prompt'), outputs=gr.Textbox(label='Generated-output'))
+iface.launch(share=True)