llama.cpp
llama-dl
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llama.cpp | llama-dl | |
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766 | 17 | |
55,117 | 3,386 | |
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9.9 | 8.8 | |
6 days ago | about 1 year ago | |
C++ | Shell | |
MIT License | GNU General Public License v3.0 only |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
llama.cpp
- Llama.cpp Working on Support for Llama3
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Embeddings are a good starting point for the AI curious app developer
Have just done this recently for local chat with pdf feature in https://recurse.chat. (It's a macOS app that has built-in llama.cpp server and local vector database)
Running an embedding server locally is pretty straightforward:
- Get llama.cpp release binary: https://github.com/ggerganov/llama.cpp/releases
- Mixtral 8x22B
- Llama.cpp: Improve CPU prompt eval speed
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Ollama 0.1.32: WizardLM 2, Mixtral 8x22B, macOS CPU/GPU model split
Ah, thanks for this! I can't edit my parent comment that you replied to any longer unfortunately.
As I said, I only compared the contributors graphs [0] and checked for overlaps. But those apparently only go back about year and only list at most 100 contributors ranked by number of commits.
[0]: https://github.com/ollama/ollama/graphs/contributors and https://github.com/ggerganov/llama.cpp/graphs/contributors
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KodiBot - Local Chatbot App for Desktop
KodiBot is a desktop app that enables users to run their own AI chat assistants locally and offline on Windows, Mac, and Linux operating systems. KodiBot is a standalone app and does not require an internet connection or additional dependencies to run local chat assistants. It supports both Llama.cpp compatible models and OpenAI API.
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Mixture-of-Depths: Dynamically allocating compute in transformers
There are already some implementations out there which attempt to accomplish this!
Here's an example: https://github.com/silphendio/sliced_llama
A gist pertaining to said example: https://gist.github.com/silphendio/535cd9c1821aa1290aa10d587...
Here's a discussion about integrating this capability with ExLlama: https://github.com/turboderp/exllamav2/pull/275
And same as above but for llama.cpp: https://github.com/ggerganov/llama.cpp/issues/4718#issuecomm...
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The lifecycle of a code AI completion
For those who might not be aware of this, there is also an open source project on GitHub called "Twinny" which is an offline Visual Studio Code plugin equivalent to Copilot: https://github.com/rjmacarthy/twinny
It can be used with a number of local model services. Currently for my setup on a NVIDIA 4090, I'm running both the base and instruct model for deepseek-coder 6.7b using 5_K_M Quantization GGUF files (for performance) through llama.cpp "server" where the base model is for completions and the instruct model for chat interactions.
llama.cpp: https://github.com/ggerganov/llama.cpp/
deepseek-coder 6.7b base GGUF files: https://huggingface.co/TheBloke/deepseek-coder-6.7B-base-GGU...
deepseek-coder 6.7b instruct GGUF files: https://huggingface.co/TheBloke/deepseek-coder-6.7B-instruct...
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More Agents Is All You Need: LLMs performance scales with the number of agents
If I'm reading this correctly, they had to discard Llama 2 answers and only use GPT-3.5 given answers to test the hypothesis.
GPT-3.5 answering questions through the OAI API alone is not an acceptable method of testing problem solving ability across a range of temperatures. OpenAI does some blackbox wizardry on their end.
There are many complex and clever sampling techniques for which temperature is just one (possibly dynamic) component
One example from the llama.cpp codebase is dynamic temperature sampling
https://github.com/ggerganov/llama.cpp/pull/4972/files
Not sure what you mean by whole model state given that there are tens of thousands of possible tokens and the models have billions of parameters in XX,XXX-dimensional space. How many queries across how many sampling methods might you need? Err..how much time? :)
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Hosting Your Own AI Chatbot on Android Devices
git clone https://github.com/ggerganov/llama.cpp.git
llama-dl
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Gitlab confirms it's removed Suyu, a fork of Nintendo Switch emulator Yuzu
There seems to be some confusion here. Let me step in as someone who has gone through this.
My repo https://github.com/shawwn/llama-dl was taken down last March by Facebook. They asserted copyright over LLaMA, which is obviously bogus since it was trained on data they do not own the copyright to. I was bummed about this, but after I mentioned on HN that I was willing to fight Meta, an anonymous person named L contacted me and sent $20k of Monero to cover legal fees. I was also contacted by an amazing lawyer who wanted to represent me in this. I was absurdly fortunate on both counts.
He drafted a counternotice, we sent it, and then my repo was restored within a week or so.
GitHub had no choice in the matter. Legally this is a required process. Ditto for GitLab. Both are US companies.
When YouTube-dl was taken down some time ago by a DMCA, Nat went to bat and got it restored, and GitHub made some sort of pledge to cover legal fees associated with bogus takedown requests.
Here’s the shitty part for this particular situation. A case can be made that the emulator is for the purpose of circumventing copyright protection mechanisms. This, sadly, is a solid legal basis for issuing a lawful takedown, as much as we all absolutely despise that idea. It’s pretty clear cut; Nintendo doesn’t want Switch games to be run on non-Nintendo platforms, and the emulator seeks to enable Switch games to be run on any platform. Therefore, the intent of the emulator is to circumvent Nintendo’s protection mechanisms.
So where does this leave us? Well, the team can file a counternotice. GitLab will restore the repo. But that opens up the team to a lawsuit by Nintendo. And as much as I want to stand up to bullies, there’s a difference between standing up to a guy shoving a kid in a locker vs standing up to a Silverback gorilla charging at you. Nintendo’s legal history implies the latter.
Welcome to Nintendo pain. The Smash community has been dealing with Nintendo’s BS for decades now. They shut down tournaments that use emulators for Smash Melee. And no one can do anything, because it’s their legal right to do so.
- [Chat Gpt] Metas LLaMA LLM ist durchgesickert – Führen Sie unzensierte KI auf Ihrem Heim-PC aus!
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Run LLaMA and Alpaca on your computer
Your philosophical argument is interesting, but what the op was saying was one of the linked repos in inaccessible due to DMCA: https://github.com/shawwn/llama-dl
So while what you say may be true the DMCA seems to have worth for these orgs because they can get code removed by the host, who is uninterested in litigating, and the repo owner likely is even less capable of litigating the DMCA.
Unfortunately as a tool of fear and legal gridlock DMCA has shown itself to be very useful to those with ill intent.
- Meta DMCAs llama-dl Repository
- Load LLaMA Models Instantly
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Is there some sort of open-source equivalent of this?
Here are some useful links: https://github.com/shawwn/llama-dl and https://rentry.org/llama-tard-v2#tips-and-tricks
- FLiP Stack Weekly for 13 March 2023
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Using LLaMA with M1 Mac and Python 3.11
Sure. You can get models with magnet link from here https://github.com/shawwn/llama-dl/
To get running, just follow these steps https://github.com/ggerganov/llama.cpp/#usage
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New JailBreak prompt + How to stop flagging/blocking!
https://rentry.org/llama-tard-v2#tips-and-tricks https://github.com/shawwn/llama-dl
- LLaMA, o ChatGPT da Meta vaza na internet e já pode ser baixada
What are some alternatives?
ollama - Get up and running with Llama 2, Mistral, Gemma, and other large language models.
llama - Inference code for Llama models
gpt4all - gpt4all: run open-source LLMs anywhere
text-generation-webui - A Gradio web UI for Large Language Models. Supports transformers, GPTQ, AWQ, EXL2, llama.cpp (GGUF), Llama models.
transformers - 🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.
GPTQ-for-LLaMa - 4 bits quantization of LLaMA using GPTQ
dalai - The simplest way to run LLaMA on your local machine
ggml - Tensor library for machine learning
llama-mps - Experimental fork of Facebooks LLaMa model which runs it with GPU acceleration on Apple Silicon M1/M2
alpaca.cpp - Locally run an Instruction-Tuned Chat-Style LLM
egghead - discord bot for ai stuff