For the ludicrously fast Llama 3 70B API from @GroqInc
, get an API key from https://
console.groq.com/keys and then: llm install 'https:''//github.com/lexh/llm-groq/archive/ba9d7de74b3057b074a85fe99fe873b75519bd78.zip'
llm keys set groq
# paste API key here
llm -m groq-llama3-70b 'hi'
OPEN SOURCE
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Groq Llama 3 70B API Setup Guide and Installation
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Running Meta-Llama-3-8B Local Model on Your Laptop
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Here's the super-short version. For a ~4GB local model that should run on most laptops: brew install llm # or pipx install llm
llm install llm-gpt4all
llm -m Meta-Llama-3-8B-Instruct "Three great names for a pet emu" -
PandasAI: Generative AI for Natural Language Data Analysis
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Python library that adds Generative AI capabilities to Pandas Introducing PandasAI, now you can analyze complex data frames and plot visualizations just by using natural language
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Community Long-Context LLaMA 3 Variants: What Exists?
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Are there any long-context LLaMA 3 variants that the community has trained yet?
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Llama 3 LLM Plugins: Local Hosting and API Access Guide
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I pulled together notes on all of the LLM plugins that have worked for me for Llama 3 – both for hosting locally (I've run 8B and 70B on my 64GB M2) and access via APIs (Groq is SO FAST for that)
— Simon Willison (@simonw) 22 avril 2024
Options for accessing Llama 3 from the terminal using LLMhttps://t.co/OuG7EqCI4F pic.twitter.com/xmBisMH7IoI pulled together notes on all of the LLM plugins that have worked for me for Llama 3 – both for hosting locally (I've run 8B and 70B on my 64GB M2) and access via APIs (Groq is SO FAST for that) Options for accessing Llama 3 from the terminal using LLM https://
simonwillison.net/2024/Apr/22/ll
ama-3/
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Sakana AI Releases EvoSDXL-JP Image Generation Model
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We have released "EvoSDXL-JP," an image generation model constructed using the "Evolutionary Model Merging" proposed by Sakana AI. The constructed model supports Japanese and can generate images 10 times faster than conventional Japanese models. Blog → https://
sakana.ai/evosdxl-jp -
Meta-Llama-3-70B-Instruct Q4 Quantized Model Implementation
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I used the Meta-Llama-3-70B-Instruct.Q4_0.llamafile (quantized at Q4) file from here:
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Running Llama-3-70B-Instruct locally on M4 Mac
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Pleased to report that the Llamafile release of Llama-3-70B-Instruct works on my 64GB M4 – I had to download the 37GB file, quit a whole bunch of apps to free up RAM, then chmod 755 it, run ./Meta-Llama-3-70B-Instruct.Q4_0.llamafile and visit it on port 8080 on localhost
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Llama2 English Language Performance Comparison Analysis
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It also has hiccups in English. Llama2 does not have these.
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Llama 3 70B via Ollama: GPT-4 quality but degradation issues
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ollama run llama3:70b It seems to run well and feels like GPT-4, with the added benefit that there’s no “limit replies as much as possible” system restriction. However it pukes itself pretty quickly and starts emitting garbage.