Vram 16gig poor. What models do I test?
📰 Reddit r/LocalLLaMA
Discover suitable LLM models for a 5060ti 16gig GPU with 64gig DDR4 RAM for various tasks like coding, chatting, and vision processing
Action Steps
- Test LLaMA models for coding tasks using opencode/smallcode
- Evaluate the performance of LLaMA and other models for chatting and conversation tasks
- Assess the capabilities of vision-focused models like Stable Diffusion for picture labeling and creation
- Explore the use of agent-based models for tool calling and roll play
- Investigate the compatibility of models like LLaMA with email readers that require context understanding, such as Hermes
Who Needs to Know This
Developers and researchers working with LLMs can benefit from this information to optimize their model selection for specific tasks, ensuring efficient use of their hardware resources
Key Insight
💡 Choosing the right LLM model for your specific tasks and hardware can significantly improve performance and efficiency
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🤖 Find the perfect LLM model for your 5060ti 16gig GPU! 🚀
Key Takeaways
Discover suitable LLM models for a 5060ti 16gig GPU with 64gig DDR4 RAM for various tasks like coding, chatting, and vision processing
Full Article
I just got myself a 5060ti 16gig, this along with my 64gig ddr4 3200mhz ram on Linux. What models should I test for, coding with opencode/smallcode, chatting, lesson planning (creative, brainstorming), vision for pictures labelling, picture creation, for agent use with good tool calling, roll play, email reader (needs context understand, and the ability to be used in hermes) I've played with lots of cloud models and currently using chatgpt and deep
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