upload app

app.py

@@ -0,0 +1,49 @@
+import gradio as gr
+from transformers import AutoTokenizer, TFAutoModelForCausalLM
+
+
+SAVED_CHECKPOINT = 'mikegarts/distilgpt2-erichmariaremarque'
+MIN_WORDS = 60
+
+
+def get_model():
+    model = TFAutoModelForCausalLM.from_pretrained(SAVED_CHECKPOINT)
+    tokenizer = AutoTokenizer.from_pretrained(SAVED_CHECKPOINT)
+    return model, tokenizer
+
+
+def generate(prompt):
+    model, tokenizer = get_model()
+
+    input_context = prompt
+    input_ids = tokenizer.encode(input_context, return_tensors="tf")
+
+    outputs = model.generate(
+        input_ids=input_ids,
+        max_length=MIN_WORDS,
+        temperature=0.7,
+        num_return_sequences=1,
+        do_sample=True
+    )
+
+    return tokenizer.decode(outputs[0], skip_special_tokens=True).rsplit('.', 1)[0] + '.'
+
+
+def predict(prompt):
+    return generate(prompt=prompt)
+
+
+title = "What would Remarques say?"
+description = """
+The bot was trained to complete your prompt as if it was a begining of a paragraph of Remarque's book.
+<img src="https://upload.wikimedia.org/wikipedia/commons/1/10/Bundesarchiv_Bild_183-R04034%2C_Erich_Maria_Remarque_%28cropped%29.jpg" align=center width=200px>
+"""
+
+gr.Interface(
+    fn=predict,
+    inputs="textbox",
+    outputs="text",
+    title=title,
+    description=description,
+    examples=[["I was drinking because"], ["Who is Karl for me?"]]
+).launch(debug=True)