Create germmacode/code_generator.py

germmacode/code_generator.py

@@ -0,0 +1,25 @@
+import transformers
+
+def generate(idea):
+    # Load the code generation model
+    model_name = "Salesforce/codegen-350M-mono"
+    model = transformers.AutoModelForCausalLM.from_pretrained(model_name)
+    tokenizer = transformers.AutoTokenizer.from_pretrained(model_name)
+
+    # Generate the code
+    input_text = f"""
+    # Idea: {idea}
+
+    # Code:
+    """
+    input_ids = tokenizer.encode(input_text, return_tensors="pt")
+    output_sequences = model.generate(
+        input_ids=input_ids,
+        max_length=1024,
+        num_return_sequences=1,
+        no_repeat_ngram_size=2,
+        early_stopping=True,
+    )
+    generated_code = tokenizer.decode(output_sequences[0], skip_special_tokens=True)
+
+    return generated_code