Update app.py

app.py

@@ -1,4 +1,17 @@
+
 import gradio as gr
+
+title = "GPT-J-6B"
+description = "GPT-J 6B, a transformer model trained using Ben Wang's Mesh Transformer JAX.'6B' is the number of trainable parameters. Add your text, or click one of the examples to load them."
+article = "<p style='text-align: center'><a href='https://github.com/kingoflolz/mesh-transformer-jax' target='_blank'>GPT-J-6B: A 6 Billion Parameter Autoregressive Language Model</a></p>"
+examples = [
+    ['A space ranger encounters a strange silhouette.'],
+    ["A day on Saturn is 10 hours and 14 minutes."],
+    ["There's no oxygen on Saturn, but roughly 75% hydrogen and 25% helium."]
+]
+gr.Interface.load("huggingface/rexwang8/qilin-lit-6b", inputs=gr.inputs.Textbox(lines=5, label="Input Text"),title=title,description=description,article=article, examples=examples,enable_queue=True).launch()
+
+'''
 import os
 from transformers import AutoTokenizer, AutoModelForCausalLM
 
@@ -6,15 +19,14 @@ def GenerateResp(prompt):
     model = AutoModelForCausalLM.from_pretrained('rexwang8/qilin-lit-6b')
     tokenizer = AutoTokenizer.from_pretrained('rexwang8/qilin-lit-6b')
     
-    #prompt = '''I had eyes but couldn't see Mount Tai!'''
-    
     input_ids = tokenizer.encode(prompt, return_tensors='pt')
     output = model.generate(input_ids, do_sample=True, temperature=1.0, top_p=0.9, repetition_penalty=1.2, max_length=len(input_ids[0])+100, pad_token_id=tokenizer.eos_token_id)
     generated_text = tokenizer.decode(output[0])
     return generated_text
-
-
+'''
+'''
 inputbox = gr.Textbox(label="Input",lines=3,placeholder='Type anything. The longer the better since it gives Qilin more context. Qilin is trained on english translated eastern (mostly chinese) webnovels.')
 outputbox = gr.Textbox(label="Qilin-Lit-6B",lines=8)
 iface = gr.Interface(fn=GenerateResp, inputs="text", outputs="text")
 iface.launch()
+'''