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andersonbcdefg

45 karma · joined May 13, 2020

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andersonbcdefg··on Don't Build an RL Environment Startup
~all the frontier and near-frontier labs are buying them from what I gather (OpenAI, Anthropic, Meta, Amazon AGI, xAI, etc.)
andersonbcdefg··on Show HN: AIQ – A no-frills CLI for embeddings and text classification
Great suggestion, I'll look into that. My expectation is that this library would not be state-of-the-art compared to training on labeled data (the intended purpose is building models where labels aren't available, if you have labels, it's obviously good to use the labels, ha). But it would be interesting to see how much of the performance is retained relative to training on the gold labels.
andersonbcdefg··on Show HN: AIQ – A no-frills CLI for embeddings and text classification
Hello! Yes, the other person who replied to you beat me to it, but this already works with any LLM provider that is OpenAI-compatible, via providing a custom API base URL. For hosted providers, this includes Together AI, Mistral, and I think even Google has an OpenAI-compatible endpoint for Gemini now. This should also work with self-hosted options like vLLM and Ollama. I led with OpenAI in the quickstart as this is the provider that most people are likely familiar with, and easiest to get started.
andersonbcdefg··on Show HN: LeanRL: Fast PyTorch RL with Torch.compile and CUDA Graphs
This is awesome Vincent, Tensordict x CleanRL x torch.compile is the most ambitious crossover