Update app.py

app.py

@@ -1,14 +1,18 @@
-from transformers import pipeline
+from transformers import pipeline, AutoTokenizer, AutoModelForCausalLM
 
-# Load the code generation model (for example, CodeGen or GPT-Neo)
-model_name = "deepseek-ai/deepseek-coder-6.7b-instruct"  # Example model from Hugging Face
-generator = pipeline('text-generation', model=model_name)
+# Load tokenizer and model
+model_name = "deepseek-ai/deepseek-coder-6.7b-instruct"
+tokenizer = AutoTokenizer.from_pretrained(model_name, trust_remote_code=True)
+model = AutoModelForCausalLM.from_pretrained(model_name, trust_remote_code=True)
 
-# Input description (your task or goal)
-text_description = "Create a Python script in Blender to animate a rotating 3D cube."
+# Create a pipeline
+generator = pipeline("text-generation", model=model, tokenizer=tokenizer)
 
-# Generate code based on the description
-generated_code = generator(text_description, max_length=150)
+# Input description
+text_description = "<|user|>\nCreate a Python script in Blender to animate a rotating 3D cube.\n<|assistant|>"
 
-# Output the generated code
-print(generated_code[0]['generated_text'])
+# Generate code
+generated = generator(text_description, max_new_tokens=200, do_sample=True, temperature=0.7)
+
+# Print result
+print(generated[0]['generated_text'].replace(text_description, '').strip())