Create app.py

app.py

@@ -0,0 +1,34 @@
+import gradio as gr
+from transformers import AutoTokenizer, AutoModelForCausalLM
+
+# Load model and tokenizer
+model_name = "shenzye46/SmolLM-135M-fine-tuned-recepie"  # Replace with your model name
+tokenizer_name = "HuggingFaceTB/SmolLM-135M"
+
+def load_model_and_tokenizer():
+    tokenizer = AutoTokenizer.from_pretrained(model_name)
+    model = AutoModelForCausalLM.from_pretrained(tokenizer_name)
+    return tokenizer, model
+
+tokenizer, model = load_model_and_tokenizer()
+
+def generate_recipe(recipe_name):
+    """Generate cooking method given a recipe name."""
+    prompt = f"Recipe Name: {recipe_name}\nInstructions: "
+    inputs = tokenizer(prompt, return_tensors="pt")
+    outputs = model.generate(inputs["input_ids"], max_length=512, num_return_sequences=1, do_sample=True)
+    generated_text = tokenizer.decode(outputs[0], skip_special_tokens=True)
+    # Return only the method part, splitting after 'Method:'
+    return generated_text.split("Method:")[-1].strip()
+
+# Create Gradio interface
+interface = gr.Interface(
+    fn=generate_recipe,
+    inputs=gr.Textbox(label="Recipe Name", placeholder="Enter the recipe name, e.g., Chocolate Cake"),
+    outputs=gr.Textbox(label="Cooking Method"),
+    title="Recipe Generator",
+    description="Enter the name of a recipe, and the model will generate the method to cook it!",
+)
+
+# Launch the app
+interface.launch()