llama-dl
ggml
llama-dl | ggml | |
---|---|---|
17 | 69 | |
3,386 | 9,725 | |
- | - | |
8.8 | 9.8 | |
about 1 year ago | 6 days ago | |
Shell | C | |
GNU General Public License v3.0 only | MIT License |
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-dl
-
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!
-
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
-
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
-
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
-
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
ggml
-
LLMs on your local Computer (Part 1)
git clone https://github.com/ggerganov/ggml cd ggml mkdir build cd build cmake .. make -j4 gpt-j ../examples/gpt-j/download-ggml-model.sh 6B
-
GGUF, the Long Way Around
Cool. I was just learning about GGUF by creating my own parser for it based on the spec https://github.com/ggerganov/ggml/blob/master/docs/gguf.md (for educational purposes)
-
Ask HN: People who switched from GPT to their own models. How was it?
If you don't care about the details of how those model servers work, then something that abstracts out the whole process like LM Studio or Ollama is all you need.
However, if you want to get into the weeds of how this actually works, I recommend you look up model quantization and some libraries like ggml[1] that actually do that for you.
[1] https://github.com/ggerganov/ggml
- GGUF File Format
-
Google just shipped libggml from llama-cpp into its Android AICore
Because the library is called ggml, but it supports gguf.
-
Q-Transformer
Apparently this guy like a bunch of others like https://github.com/ggerganov/ggml are implementing transformers from papers for people that want them. Pretty cool.
-
[P] Inference Vision Transformer (ViT) in plain C/C++ with ggml
You can access it here: https://github.com/staghado/vit.cpp It has been added to the ggml library on GitHub: https://github.com/ggerganov/ggml
-
Falcon 180B Released
https://github.com/ggerganov/ggml
One note is that prompt ingestion is extremely slow on CPU compared to GPU. So short prompts are fine (as tokens can be streamed once the prompt is ingested), but long prompts feel extremely sluggish.
-
Stable Diffusion in pure C/C++
I did a quick run under profiler and on my AVX2-laptop the slowest part (>50%) was matrix multiplication (sgemm).
In current version of GGML if OpenBLAS is enabled, they convert matrices to FP32 before running sgemm.
If OpenBLAS is disabled, on AVX2 plaftorm they convert FP16 to FP32 on every FMA operation, which even worse (due to repetition). After that, both ggml_vec_dot_f16 and ggml_vec_dot_f32 took first place in profiler.
Source: https://github.com/ggerganov/ggml/blob/master/src/ggml.c#L10...
-
Accessing Llama 2 from the command-line with the LLM-replicate plugin
For those getting started, the easiest one click installer I've used is Nomic.ai's gpt4all: https://gpt4all.io/
This runs with a simple GUI on Windows/Mac/Linux, leverages a fork of llama.cpp on the backend and supports GPU acceleration, and LLaMA, Falcon, MPT, and GPT-J models. It also has API/CLI bindings.
I just saw a slick new tool https://ollama.ai/ that will let you install a llama2-7b with a single `ollama run llama2` command that has a very simple 1-click installer for Apple Silicon Mac (but need to build from source for anything else atm). It looks like it only supports llamas OOTB but it also seems to use llama.cpp (via Go adapter) on the backend - it seemed to be CPU-only on my MBA, but I didn't poke too much and it's brand new, so we'll see.
For anyone on HN, they should probably be looking at https://github.com/ggerganov/llama.cpp and https://github.com/ggerganov/ggml directly. If you have a high-end Nvidia consumer card (3090/4090) I'd highly recommend looking into https://github.com/turboderp/exllama
For those generally confused, the r/LocalLLaMA wiki is a good place to start: https://www.reddit.com/r/LocalLLaMA/wiki/guide/
I've also been porting my own notes into a single location that tracks models, evals, and has guides focused on local models: https://llm-tracker.info/
What are some alternatives?
llama.cpp - LLM inference in C/C++
llama - Inference code for Llama models
alpaca.cpp - Locally run an Instruction-Tuned Chat-Style LLM
text-generation-webui - A Gradio web UI for Large Language Models. Supports transformers, GPTQ, AWQ, EXL2, llama.cpp (GGUF), Llama models.
alpaca-lora - Instruct-tune LLaMA on consumer hardware
transformers - 🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.
mlc-llm - Enable everyone to develop, optimize and deploy AI models natively on everyone's devices.
dalai - The simplest way to run LLaMA on your local machine
llama-mps - Experimental fork of Facebooks LLaMa model which runs it with GPU acceleration on Apple Silicon M1/M2
llm - An ecosystem of Rust libraries for working with large language models