llama.cpp
safetensors
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llama.cpp | safetensors | |
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769 | 31 | |
56,891 | 2,442 | |
- | 14.8% | |
10.0 | 8.2 | |
1 day ago | 5 days ago | |
C++ | Python | |
MIT License | Apache License 2.0 |
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
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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
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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...
safetensors
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Llamafile lets you distribute and run LLMs with a single file
The ML field is doing work in that area: https://github.com/huggingface/safetensors
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Hugging Face raises $235M from investors including Salesforce and Nvidia
FYI the file format, safetensors, was proposed, developed and maintained by HF, and involved people from groups such as Eleuther and Stability for external security audits.
https://github.com/huggingface/safetensors https://huggingface.co/blog/safetensors-security-audit
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I Made Stable Diffusion XL Smarter by Finetuning It on Bad AI-Generated Images
Thank you for note on this. I had not heard there were already trojan horse malware being slipped into tensor files as python scripts. Apparently torch pickle uses eval on the tensor file with no filter.
Heard surprisingly little commentary on this topic. The full explanation of how Safetensors are "Safe" can be found from the developer at: https://github.com/huggingface/safetensors/discussions/111
- Pickle safety in Python
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What makes .safetensors files safe?
Here the developer goes into some detail about what kinds of protections .safetensor files have : https://github.com/huggingface/safetensors/discussions/111
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Security PSA: huggingface models are code. not just data.
Use the safetensors format, which allows safe persistence and loading of models for common libraries - TensorFlow, PyTorch, JAX, etc. We went through external audits in the last few months (blog post). The current direction will be to have this as the default format.
- What's your favorite model. Right now I'm really enjoying dreamshaper.
- Lora, ggml, safetensors, hf, etc. Is there a glossary and guide on which model to choose?
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Stability AI Launches the First of Its StableLM Suite of Language Models
I've been diving in lately and while it's not efficient, the only way to do manage is to create a new conda/mamba environment, or a custom Docker image for all the conflicting packages.
For safety and speed, you should prefer the safetensor format: https://huggingface.co/docs/safetensors/speed
If you know what you are doing you can do your own conversions: https://github.com/huggingface/safetensors or for safety, https://huggingface.co/spaces/diffusers/convert
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CKPT to Safetensors
GitHub - huggingface/safetensors: Simple, safe way to store and distribute tensors
What are some alternatives?
ollama - Get up and running with Llama 3, Mistral, Gemma, and other large language models.
stable-diffusion-webui - Stable Diffusion web UI
gpt4all - gpt4all: run open-source LLMs anywhere
Safe-and-Stable-Ckpt2Safetensors-Conversion-Tool-GUI - Convert your Stable Diffusion checkpoints quickly and easily.
text-generation-webui - A Gradio web UI for Large Language Models. Supports transformers, GPTQ, AWQ, EXL2, llama.cpp (GGUF), Llama models.
InvokeAI - InvokeAI is a leading creative engine for Stable Diffusion models, empowering professionals, artists, and enthusiasts to generate and create visual media using the latest AI-driven technologies. The solution offers an industry leading WebUI, supports terminal use through a CLI, and serves as the foundation for multiple commercial products.
GPTQ-for-LLaMa - 4 bits quantization of LLaMA using GPTQ
Stable-Diffusion-Pickle-Scanner-GUI - Pickle Scanner GUI
ggml - Tensor library for machine learning
stable-diffusion-webui-model-toolkit - A Multipurpose toolkit for managing, editing and creating models.
alpaca.cpp - Locally run an Instruction-Tuned Chat-Style LLM
alpaca_lora_4bit