local.ai
llama.cpp
| local.ai | llama.cpp | |
|---|---|---|
| 4 | 773 | |
| 520 | 56,891 | |
| - | - | |
| 8.7 | 10.0 | |
| 7 months ago | 4 days ago | |
| TypeScript | C++ | |
| GNU General Public License v3.0 only | MIT License |
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local.ai
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Why does GPT4all respond so slowly on my machine?
I tried to launch gpt4all on my laptop with 16gb ram and Ryzen 7 4700u. Gpt4all doesn't work properly. It uses igpu at 100% level instead of using cpu. And it can't manage to load any model, i can't type any question in it's window. Faraday.dev, secondbrain.sh, localai.app, lmstudio.ai, rwkv runner, LoLLMs WebUI, kobold cpp: all these apps run normally. Only gpt4all and oobabooga fail to run.
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All AI Models, from 3B to 13B running at ~0.5 tokens/s, what could be causing this?
Sidenote: can you try out localai.app and see if it's faster than oobabooga on your end? (It's all CPU inferencing as well, but just curious if there's any speed gain).
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Releasing local.ai - an LLM local playground with minimal setup
Thank you. When I first started the project and got the domain localai.app, I had no idea LocalAI was a thing. A friend of mine forwarded me a link to that project mid May, and I was like dang it, let's just add a dot and call it a day (for now...) - local "dot" ai vs LocalAI lol
llama.cpp
- Llama.cpp Bfloat16 Support
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Fine-tune your first large language model (LLM) with LoRA, llama.cpp, and KitOps in 5 easy steps
Getting started with LLMs can be intimidating. In this tutorial we will show you how to fine-tune a large language model using LoRA, facilitated by tools like llama.cpp and KitOps.
- GGML Flash Attention support merged into llama.cpp
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Phi-3 Weights Released
well https://github.com/ggerganov/llama.cpp/issues/6849
- Lossless Acceleration of LLM via Adaptive N-Gram Parallel Decoding
- 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
What are some alternatives?
LocalAI - :robot: The free, Open Source OpenAI alternative. Self-hosted, community-driven and local-first. Drop-in replacement for OpenAI running on consumer-grade hardware. No GPU required. Runs gguf, transformers, diffusers and many more models architectures. It allows to generate Text, Audio, Video, Images. Also with voice cloning capabilities.
ollama - Get up and running with Llama 3, Mistral, Gemma, and other large language models.
chatgpt-api-example - Batman/Alfred chatbot example with ChatGPT API
gpt4all - gpt4all: run open-source LLMs anywhere
pnpm - Fast, disk space efficient package manager
text-generation-webui - A Gradio web UI for Large Language Models. Supports transformers, GPTQ, AWQ, EXL2, llama.cpp (GGUF), Llama models.
qadog - QA agent that follows user stories
GPTQ-for-LLaMa - 4 bits quantization of LLaMA using GPTQ
window.ai - Use your own AI models on the web
ggml - Tensor library for machine learning
alpaca.cpp - Locally run an Instruction-Tuned Chat-Style LLM
FastChat - An open platform for training, serving, and evaluating large language models. Release repo for Vicuna and Chatbot Arena.