Create app.py

app.py

@@ -0,0 +1,28 @@
+import gradio as gr 
+from transformers import AutoTokenizer, pipeline
+import torch
+
+
+
+tokenizer = AutoTokenizer.from_pretrained("akoksal/LongForm-OPT-2.7B") 
+generate = pipeline('text-generation', model='akoksal/LongForm-OPT-2.7B', tokenizer=tokenizer)
+
+
+def predict(instruction, topp, temperature):
+    if "[EOI]" not in instruction:
+        instruction = instruction + " [EOI]"
+    x = generate(instruction,
+        do_sample=True, 
+        max_length=64, 
+        top_p=topp, 
+        num_return_sequences=1,
+        temperature=temperature
+    )[0]["generated_text"]
+    
+    return x
+
+iface = gr.Interface(fn=predict, inputs=["text",\\
+                                         gr.inputs.Slider(0, 2, default=1, label="temperature"),\
+                                         gr.inputs.Slider(0, 1, default=0.90, label="top_p")]
+                     , outputs="text")
+iface.launch()