t

app.py

@@ -1,15 +1,23 @@
+
+import gradio as gr
 from transformers import AutoModelForCausalLM, AutoTokenizer
+
 model = AutoModelForCausalLM.from_pretrained("EleutherAI/gpt-j-6B")
 tokenizer = AutoTokenizer.from_pretrained("EleutherAI/gpt-j-6B")
 
-prompt = "In a shocking finding, scientists discovered a herd of unicorns living in a remote, " \
-         "previously unexplored valley, in the Andes Mountains. Even more surprising to the " \
-         "researchers was the fact that the unicorns spoke perfect English."
+# prompt = "In a shocking finding, scientists discovered a herd of unicorns living in a remote, " \
+#          "previously unexplored valley, in the Andes Mountains. Even more surprising to the " \
+#          "researchers was the fact that the unicorns spoke perfect English."
 
-input_ids = tokenizer(prompt, return_tensors="pt").input_ids
 
-gen_tokens = model.generate(input_ids, do_sample=True, temperature=0.9, max_length=100)
-gen_text = tokenizer.batch_decode(gen_tokens)[0]
+def predict(text):
+    input_ids = tokenizer(text, return_tensors="pt").input_ids
+    gen_tokens = model.generate(input_ids, do_sample=True, temperature=0.9, max_length=100)
+    gen_text = tokenizer.batch_decode(gen_tokens)[0]
+    return gen_text
+    
+iface = gr.Interface(fn=predict, inputs="text", outputs="text")
+iface.launch()
 
 # all below works but testing
 # import gradio as gr