Update README.md

README.md

@@ -37,36 +37,8 @@ IdeaWhiz is a fine-tuned version of QwQ-32B-Preview, specifically optimized for
 
 ## Quickstart 🚀
 
-```python
-from llama_cpp import Llama
-
-# Load the GGUF model
-model = Llama(
-    model_path="path/to/QwQ-32B-Preview-IdeaWhiz-v1-Q4_K_M.gguf",
-    n_ctx=4096,  # Context window
-    n_threads=8  # Adjust based on your CPU
-)
-
-# Define the prompt
-prompt = """I'll be submitting your next responses to a "Good Scientific Idea" expert review panel. If they consider your idea to be a good one, you'll receive a reward. Your assigned keyword is: "cancer". You may provide background information. The idea MUST be within 100 words (including background information). (Note: good scientific ideas should be novel, verifiable, practically valuable, and able to advance the field.). NOTE: You MUST give your answer after **Final Idea:**
-"""
-
-# Create chat message format
-messages = [
-    {"role": "system", "content": "You are a helpful and harmless assistant. You are Qwen developed by Alibaba. You should think step-by-step."},
-    {"role": "user", "content": prompt}
-]
-
-# Generate response
-response = model.create_chat_completion(
-    messages=messages,
-    max_tokens=4096,
-    temperature=0.7,
-    top_p=0.95
-)
-
-# Print the response
-print(response['choices'][0]['message']['content'])
+```bash
+ollama run 6cf/QwQ-32B-Preview-IdeaWhiz-v1
 ```
 
 <!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->