Llama: update history
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title: 'A Brief History of Local Llamas'
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title: 'A Brief History of Local Llamas'
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description: 'A Brief History of Local Llamas'
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description: 'A Brief History of Local Llamas'
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updateDate: 'Jan 01 2024'
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updateDate: 'Feb 11 2024'
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heroImage: '/images/llama/tiny-llama-logo.avif'
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heroImage: '/images/llama/tiny-llama-logo.avif'
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---
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@ -161,4 +161,19 @@ the turning point where open source models finally break ahead of commercial
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models. However as of writing, it's very unclear how the community will break
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models. However as of writing, it's very unclear how the community will break
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through GPT4, the llama that remains uncontested in practice.
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through GPT4, the llama that remains uncontested in practice.
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#### Early 2024
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This is where we currently are! Hence, things are just dates for now. We'll see
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how much impact they have in a retrospective:
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- 2024-01-22: Bard with Gemini-Pro defeats all models except GPT4-Turbo in
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chatbot arena. This is seen as questionably fair, since bard has internet
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access.
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- 2024-01-29: miqu gets released. This is a suspected Mistral_Medium leak.
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Despite only having a 4bit-quantized version, it's ahead of all current
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locallamas.
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- 2024-01-30: Yi-34B is the largest local llama for language-vision. LLaVA 1.6
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based on top of it sets new records in vision performance.
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- 2024-02-08: Google releases Gemini Advanced, a GPT4 competitor with similar
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pricing. Public opinion seems to be that it's quite a bit worse that GPT4,
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except that it's less censored and much better at creative writing.
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@ -1,7 +1,7 @@
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---
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---
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title: 'Local Llama Quickstart'
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title: 'Local Llama Quickstart'
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description: 'A collection of guides to get started with local llamas'
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description: 'A collection of guides to get started with local llamas'
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updateDate: 'Dec 31 2023'
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updateDate: 'Jan 28 2024'
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heroImage: '/images/llama/llama-cool.avif'
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heroImage: '/images/llama/llama-cool.avif'
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@ -49,6 +49,7 @@ anyone looking to get caught up with the field.
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- [Karpathy builds and trains a llama](https://www.youtube.com/watch?v=kCc8FmEb1nY)
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- [Karpathy builds and trains a llama](https://www.youtube.com/watch?v=kCc8FmEb1nY)
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- [Build a llama DIY by freecodecamp](https://www.youtube.com/watch?v=UU1WVnMk4E8)
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- [Build a llama DIY by freecodecamp](https://www.youtube.com/watch?v=UU1WVnMk4E8)
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- [Understanding different quantization methods](https://www.youtube.com/watch?v=mNE_d-C82lI)
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- [Understanding different quantization methods](https://www.youtube.com/watch?v=mNE_d-C82lI)
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- [LLM workshop](https://github.com/mlabonne/llm-course)
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#### Servers
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#### Servers
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- [Ollama.ai](https://ollama.ai/)
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- [Ollama.ai](https://ollama.ai/)
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@ -58,6 +59,8 @@ anyone looking to get caught up with the field.
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#### GPU stuff
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#### GPU stuff
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- [Choosing a GPU for deeplearning](https://timdettmers.com/2023/01/30/which-gpu-for-deep-learning/)
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- [Choosing a GPU for deeplearning](https://timdettmers.com/2023/01/30/which-gpu-for-deep-learning/)
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- [Last gen servers for
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AI](https://www.kyleboddy.com/2024/01/28/building-deep-learning-machines-unorthodox-gpus/)
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#### Cloud renting
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#### Cloud renting
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- [Kaggle](https://kaggle.com) - 30h/week free, enough VRAM for 7B models
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- [Kaggle](https://kaggle.com) - 30h/week free, enough VRAM for 7B models
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@ -29,7 +29,7 @@ const posts = (await getCollection('unix')).sort(
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</h1>
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</h1>
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<p
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<p
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class="text-center mb-4 text-lg">
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class="text-center mb-4 text-lg">
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Over the past few years, I've extenstively configured at
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Over the past few years, I've extenstively configured and
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learned about using MacOS, Linux, and even some BSD
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learned about using MacOS, Linux, and even some BSD
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systems. Along the way I documented some of the fun aspects
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systems. Along the way I documented some of the fun aspects
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of learning Unix. The code for most guides is part of my
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of learning Unix. The code for most guides is part of my
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