This VIBECODING LLM Runs LOCALLY! 🤯
AI Summary
Video Summary: Open Hands Model for Coding Tasks
- Introduction to Open Hands Model:
- Developed by All Hands; focused on coding tasks.
- The 7 billion parameter model offers significant capabilities, scoring 37.2% on SWB bench, outperforming many larger models.
- Performance Insights:
- Even with a smaller model, great coding results can be achieved.
- Demonstrated examples of the model’s performance and output quality.
- Model Training:
- Based on the quen coded 2.5 instruct 32 billion parameter model.
- Utilizes reinforcement learning principles from the S SWIM paper.
- Benchmarking:
- Compares favorably with older models like Deepseek R3.
- Discussion of context window limitations for local setups.
- Usage Instructions:
- Available on Hugging Face.
- Example commands for downloading and running the model locally in LM Studio.
- Recommendations on version selection based on hardware capabilities.
- Coding Examples:
- Successfully generates a working HTML5 landing page for “Little Coder Labs”.
- Responds to varied coding tasks with different levels of success.
- Practical applications include creating animations and Pygame projects.
- Demonstrates solving Stack Overflow questions, showcasing versatility and adaptability.
- Final Thoughts:
- Encouragement to test and utilize the model for coding tasks locally, suggesting it functions well without server dependence.
- Invitation for viewer feedback on the model’s performance and results.