Create app.py

app.py

@@ -0,0 +1,23 @@
+import gradio as gr
+import json
+import requests
+from transformers import pipeline
+from transformers import AutoTokenizer, AutoModelForCausalLM
+
+model_name = 'Pyg'
+tokenizer = AutoTokenizer.from_pretrained("TheBloke/Pygmalion-7B-SuperHOT-8K-GPTQ")
+model = AutoModelForCausalLM.from_pretrained("TheBloke/Pygmalion-7B-SuperHOT-8K-GPTQ")
+
+pipe = pipeline("text-generation", model="TheBloke/Pygmalion-7B-SuperHOT-8K-GPTQ")
+
+def generate_text(input_text):
+    input_ids = tokenizer.encode(input_text, return_tensors='pt')
+    outputs = model.generate(input_ids, max_length=150, num_return_sequences=1, pad_token_id=tokenizer.eos_token_id)
+    text = tokenizer.decode(outputs[0], skip_special_tokens=True)
+    return text
+
+iface = gr.Interface(fn=generate_text, 
+                      inputs=gr.inputs.Textbox(lines=5, placeholder='Enter text here...'), 
+                      outputs=gr.outputs.Textbox())
+
+iface.launch()