If you're interested in: – Python – ML/AI Engineering Find me → @akshay_pachaar Everyday, I share tutorials on these topics!
@akshay_pachaar
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All Top AI Models in One Subscription Deal
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Get all the best models under a one subscription.
— Akshay 🚀 (@akshay_pachaar) 9 février 2025
This is the best deal you'll find.
• GPT 4o / o1-preview / o1-mini
• Claude Sonnet
• Gemini 2.0 Flash
• Grok
Also includes top open-source LLMs
• Llama 3.2
• Qwen 2.5
• DeepSeek
• DeepSeek-Fast
I have shared link to… pic.twitter.com/4o8xmoQj3bGet all the best models under a one subscription. This is the best deal you'll find. • GPT 4o / o1-preview / o1-mini
• Claude Sonnet
• Gemini 2.0 Flash
• Grok Also includes top open-source LLMs • Llama 3.2
• Qwen 2.5
• DeepSeek
• DeepSeek-Fast I have shared link to -
Build Your Own Reasoning Models with Step by Step Breakdown
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Build your own reasoning models! Great step by step breakdown Avi!
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Deepseek Distilled Qwen: Smaller Model with Good Performance
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Try deepseek distilled Qwen, much smaller and reasonably good.
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Using Ollama for Testing and vLLM for Production Serving
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I use ollama most of the times for testing and prototyping and then vLLM when i need to serve it.
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Learning RAG, LLMs, AI Agents, and ML/AI Engineering
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Want to learn more about: – RAG – LLMs – AI Agents – ML/AI Engineering Find me →
@akshay_pachaar -
Multi-Agent Pattern: Specialized Agents Working Together for Results
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Multi-Agnet Pattern Multiple specialized agents working together—each with its own role! Imagine an engineering team, the PM sets goals, the Tech Lead designs, the Developer codes, and the DevOps Engineer handles deployment. Together, they deliver a unified product!
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Planning Pattern: Task Breakdown and Strategic Thinking for AI
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Planning Pattern This is all about task breakdown & strategic thinking. Instead of tackling a big request in one go, the AI creates a roadmap: – subdivides tasks
– outlines objectives Just like a project manager organizing a complex workflow. -
ReAct: Combining Reflection and Tool Use for Agents
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ReAct (Reasoning and Acting) ReAct combines Reflection and Tool use patterns. Now the agent can reflect on both the LLM-generated outputs and the results of its interactions with the external world using tools. One of the most popular and powerful patterns used today.