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DeepSeek is an amazing product but has few issues: 1. Data is used for training 2. Context window is rather small and doesn't fit as well large codebase I ke
by siscia 2y ago
DeepSeek is an amazing product but has few issues:
1. Data is used for training
2. Context window is rather small and doesn't fit as well large codebase
I keep saying this over and over in all the content I create, the valu of coding with AI will come from working on big, complex, legacy codebases. Not from flashy demo where you create a to-do app.
For that you need solid models with big context and private inference.
- MacsHeadroom 2y agoDeepSeek is open source and has a context length of 128k tokens.
- siscia 2y agoCommercial service have a context of 64k tokens, which I find quite limiting. https://api-docs.deepseek.com/quick_start/pricing https://api-docs.deepseek.com/quick_start/pricing Running it locally is quite a bit beyond the scope of being productive while coding with AI. Beside that 128k is still significantly less than Claude
- elashri 2y agoShouldn't we be comparing with other open source model? In particular since this is about llama3.3 then they have the exact context limit which is 128k [1]. Also [1] https://huggingface.co/meta-llama/Llama-3.3-70B-Instruct https://huggingface.co/meta-llama/Llama-3.3-70B-Instruct
- siscia 2y agoWhy? Whenever using a model to be more effective as a developer I don't particularly care if the model is open source or closed source. I would love to use open source models as well, but the convenience to just plug an API against some endpoints in unbeatable.