Unlocking the Full Potential of Local LLMs: A Call to Innovators!
Are you navigating the challenges of local language models (LLMs) like Ollama? If so, you’re not alone. Many enthusiasts are hitting walls with small context windows and the absence of persistent memory. Let’s explore effective solutions!
Key Challenges:
- Limited Context Windows: Stuck with short memory spans?
- No Persistent Memory: Hard to tackle long-term projects effectively.
Seeking Proven Solutions:
I’m reaching out to those with robust local setups. Share your strategies to enhance memory and extend functionality, such as:
- Utilizing Vector Databases
- Implementing Retrieval-Augmented Generation (RAG)
- Crafting external state management loops
- Developing custom memory modules
Join the conversation! Your insights can help shape a new era of capabilities in local AI models.
Let’s collaborate and drive innovation! Please share your thoughts and experiences below.
