also, Llama3-70B is #1 on English-only, whut!!!!
OPEN SOURCE
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Ollama LLM Plugin Integration for WordPress
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Yes, ollama is a great option too – I only wrote about the options I'd got running myself, ran out of time! There's an LLM plugin for ollama here:
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LLM Plugin Directory Now Features 30 Available Plugins
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The LLM plugin directory lists 30 plugins now! https://
llm.datasette.io/en/stable/plug
ins/directory.html
… If you want to try writing your own there's a comprehensive tutorial included in the docs: https://
llm.datasette.io/en/stable/plug
ins/tutorial-model-plugin.html
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LLaMA 3-based model deployment nearing completion
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Very soon. This is one of the last things I have to get working well before we can push a LLaMA 3-based model live.
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LLaMA 3 8B Extended to 16K Token Context Window
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Training a LLaMA 3 8B that supports 16K tokens, twice the current context window. If successful, will open-source it.
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Mistral Mixtral 8x7B Mixture of Experts Architecture Course
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New short course with @MistralAI !
— Andrew Ng (@AndrewYNg) 22 avril 2024
Mistral's open-source Mixtral 8x7B model uses a "mixture of experts" (MoE) architecture. Unlike a standard transformer, an MoE model has multiple expert feed-forward networks (8 in this case), with a gating network selecting two experts at… pic.twitter.com/VFOg1dDab8New short course with @MistralAI ! Mistral's open-source Mixtral 8x7B model uses a "mixture of experts" (MoE) architecture. Unlike a standard transformer, an MoE model has multiple expert feed-forward networks (8 in this case), with a gating network selecting two experts at
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Running 4GB LLM Models on CPU with GPT4All
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I wonder if it can run the 4GB model? @nomic_ai gpt4all uses llama.cpp and can run on CPU so it might still work
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Llama 3 Access Through Multiple API Providers and Plugins
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And if you want to try Llama 3 through APIs from Perplexity, Anyscale Endpoints, Fireworks, Together AI or OpenRouter there are plugins for those too:
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Running Llama 3 70B locally with llamafile and LLM
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That starts a llamafile running Llama 3 70 B on localhost port 8080 – then talk to it from LLM like this: llm install llm-llamafile
llm -m llamafile "3 neat characteristics of a pelican" -
Running Meta-Llama-3-70B Locally with 64GB RAM
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If you have 64GB RAM:
curl -L -o Meta-Llama-3-70B-Instruct.Q4_0.llamafile 'https:''//huggingface.co/jartine/Meta-Llama-3-70B-Instruct-llamafile/resolve/main/Meta-Llama-3-70B-Instruct.Q4_0.llamafile?download=true'
chmod 755 Meta-Llama-*
./Meta-Llama-3-70B-Instruct.Q4_0.llamafile