Run Code Llama 70B in the cloud
AI Summary
Summary: Meta’s Cod Llama Release and Integration with Cloud Services
- Meta’s Cod Llama Release:
- Meta released Cod Llama, a 70 billion parameter model.
- Claims to perform slightly better than GPT-4 (67.8 vs. 67 on human eval).
- Cost-effective: 10 per million.
- Challenges and Solutions:
- Running such a large model locally is prohibitive.
- Cloud-hosted solutions like serverless APIs make it accessible and affordable.
- Using Together AI:
- Together AI offers a range of models, including Cod Llama.
- The author demonstrates setting up API keys and environment files for integration.
- A quick system template is used to generate prompts and parse outputs.
- Model Integration and Comparison:
- The author compares using OpenAI with Together AI and Any Scale.
- Shows how to override parameters to switch between service providers.
- Results indicate Together AI may edge out Any Scale in performance and cost.
- Practical Application in Development:
- The author integrates the Cod Llama model into a local development workflow.
- Demonstrates swapping models and endpoints in a production agent.
- The agent uses a mix of APIs and models for different tasks.
- Conclusion and Resources:
- The author suggests evaluating different providers based on specific needs.
- Emphasizes the ease of integrating large models into development flows.
- Offers to share notebooks on GitHub for others to experiment with.
- Final Note:
- Encourages questions and feedback on the tutorial.