MyScaleDB
axolotl
| MyScaleDB | axolotl | |
|---|---|---|
| 4 | 29 | |
| 680 | 6,105 | |
| 86.6% | 13.7% | |
| 9.0 | 9.8 | |
| 14 days ago | 2 days ago | |
| C++ | Python | |
| Apache License 2.0 | 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.
MyScaleDB
- Myscaledb: Open-source SQL vector database to build AI apps using SQL
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FLaNK AI - 01 April 2024
Vector Db built on clickhouse https://github.com/myscale/myscaledb
- Show HN: High-Performance SQL Vector Database MyScaleDB Goes Open Source
- Show HN: MyScaleDB open-sourced: a SQL vector database to Build AI APPs with SQL
axolotl
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Ask HN: Most efficient way to fine-tune an LLM in 2024?
The approach I see used is axolotl with QLoRA using cloud GPUs which can be quite cheap.
https://github.com/OpenAccess-AI-Collective/axolotl
- FLaNK AI - 01 April 2024
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LoRA from Scratch implementation for LLM finetuning
https://github.com/OpenAccess-AI-Collective/axolotl
- Optimized Triton Kernels for full fine tunes
- Axolotl
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Let’s Collaborate to Build a High-Quality, Open-Source Dataset for LLMs!
One option is to look at what Axolotl uses. They have a list of different dataset formats that they support. They're mostly in JSON with specific field names, so you could start putting a dataset together with a text editor or a JSON editor.
- Axolotl: Streamline fine-tuning of AI models
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Dataset Creation Tools?
You can save that overall set into a json file and load it up as training data in whatever you're using. I'm using axolotl for it at the moment. Though a GUI based option is probably best for the first couple of tries until you get a feel for the options.
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Progress on Reproducing Phi-1/1.5
Looking forward to the results! If it turns out the dataset is reproducible, then it might be a good candidate for ReLora training on axolotl!
What are some alternatives?
bootcamp - Dealing with all unstructured data, such as reverse image search, audio search, molecular search, video analysis, question and answer systems, NLP, etc.
signal-cli - signal-cli provides an unofficial commandline, JSON-RPC and dbus interface for the Signal messenger.
CML_AMP_Deploy-Mistral7B-CML-Native-Model - Deploy Mistral 7b model in CML using in-built, native CML models appliance
gpt-llm-trainer
tracecat - 😼 The open source alternative to Tines / Splunk SOAR. Build AI-assisted workflows, orchestrate alerts, and close cases fast.
LoRA - Code for loralib, an implementation of "LoRA: Low-Rank Adaptation of Large Language Models"
zenml - ZenML 🙏: Build portable, production-ready MLOps pipelines. https://zenml.io.
mlc-llm - Enable everyone to develop, optimize and deploy AI models natively on everyone's devices.
LMFlow - An Extensible Toolkit for Finetuning and Inference of Large Foundation Models. Large Models for All.
koboldcpp - A simple one-file way to run various GGML and GGUF models with KoboldAI's UI
OpenPipe - Turn expensive prompts into cheap fine-tuned models
xTuring - Build, customize and control you own LLMs. From data pre-processing to fine-tuning, xTuring provides an easy way to personalize open-source LLMs. Join our discord community: https://discord.gg/TgHXuSJEk6