add app.py

app.py

@@ -1,3 +1,23 @@
+from transformers import pipeline, AutoModelForCausalLM, AutoTokenizer
 import gradio as gr
 
-gr.load("models/zenai-org/SmolLM-prompt-generation").launch(share=True)
+# First define a prediction function that takes in a text prompt and returns the text completion
+
+model = pipeline("text-generation", model="zenai-org/SmolLM-prompt-generation")
+
+def predict(prompt):
+    out = model(
+        prompt,
+        max_length=77,    # Max length of the generated sequence
+        min_length=10,    # Minimum length of the generated sequence
+        do_sample=True,   # Enable sampling
+        top_k=50,         # Top-k sampling
+        top_p=0.95,       # Top-p sampling
+        temperature=0.7,  # Control the creativity of the output
+        eos_token_id=0,  # End-of-sequence token
+        # pad_token_id = tokenizer.eos_token_id,
+    )
+    return out[0]['generated_text']
+
+# Now create the interface
+gr.Interface(fn=predict, inputs="text", outputs="text", css=".footer{display:none !important}").launch(share=True)