Wait, is this real? I have been literally thinking about connecting my MacBooks for months to get a better GPU lol
@skirano
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Maestro Wins Anthropic Developer Contest with Agentic Framework
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Excited to share that Maestro, my agentic framework for Claude Opus to intelligently orchestrate subagents, is one of the winners of the official @AnthropicAI Developer contest. The best part? Opus wrote the code. I just told it what I wanted.
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Llama timeout issues resolved with Mistral model
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I know I was running into the same issue; llama requests time out pretty fast. I had to use the mistral model.
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AI Tools for Code Generation and Content Creation
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Create apps on the fly, fix or improve code, write long chunks of text, come up with research docs.
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Framework Documentation with Tokenizer Support Request
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Your documentation is super well-written, so it was really easy to convert the framework. My only request is that I would like some sort of tokenizer so I can be more precise with the amount of tokens for input and output and build a more robust system around that 🙂
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M3 Max 8B model optimization for multi-agent orchestration systems
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I have an M3 Max with 64GB. You can use the 8B model if you don't have a lot of VRAM. What I realize is that the 8B model works really well as a subagent. As long as the Orchestrator and the Refiner are the 70GB models, the whole thing works really well.
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Ollama Integration with Llama 3 Orchestration Works Well
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Some considerations:
It works surprisingly well, not many changes needed besides, of course, the different way @ollama inference works. I just had to add some more info in the prompt for the orchestrator because Llama 3 loves to yap, lol. At one point, it forgot the goal and -
Maestro-Ollama: Local Llama 3 70B Agent Framework
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Introducing Maestro-Ollama! 🦙
— Pietro Schirano (@skirano) 18 avril 2024
You can now harness the power of the Maestro framework entirely locally using Llama 3 70B via @ollama.
Let that sink in for a second, this is a model that outperforms Claude 3 Sonnet, operating as an agent, completely locally.
What a time! 🔥 pic.twitter.com/aC34Bd6F65Introducing Maestro-Ollama! You can now harness the power of the Maestro framework entirely locally using Llama 3 70B via @ollama
. Let that sink in for a second, this is a model that outperforms Claude 3 Sonnet, operating as an agent, completely locally. What a time! -
Context Size Impact on Model Intelligence and Hallucinations
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I thought the same too. I wonder what’s the rationale. I remember reading once that smaller context models tend to be smarter and hallucinate less, but I can't find the source rn. I wonder if it is related to that and if that's something that should be included in evals as well.