LaVague
mergekit
LaVague | mergekit | |
---|---|---|
4 | 6 | |
3,965 | 3,521 | |
13.4% | 18.7% | |
9.5 | 9.2 | |
1 day ago | 5 days ago | |
Python | Python | |
Apache License 2.0 | GNU Lesser 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.
LaVague
- FLaNK AI Weekly 25 March 2025
-
Show HN: Skyvern – open-source browser automation tool
There was another AI/browser automation project posted yesterday that got to the front page https://github.com/lavague-ai/LaVague
I guess the main advantage of this new project is that its probably more accurate by using computer vision, but as others has said it uses much more resources.
Costs will come down over time though.
Get ready for alot of "Back Office" jobs to be automated away.
- LaVague: Open-source Large Action Model to automate Selenium browsing
mergekit
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Language Models Are Super Mario: Absorbing Abilities from Homologous Models
For others like me who’d not heard of merging before, this seems to be one tool[0] (there may be others)
[0] https://github.com/arcee-ai/mergekit
- FLaNK AI Weekly 25 March 2025
- Tools for merging pretrained large language models
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Blending Is All You Need: Cheaper, Better Alternative to Trillion-Parameters LLM
mergekit is the tool you need to do this
https://github.com/cg123/mergekit
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Iambe-RP-20b: An uncensored L2 Frankenstein model directly trained with RP-oriented cDPO
I actually asked the creator of mergekit a question here. In his response, I learned how to use task_arithmetic to isolate the deltas. One could, in theory, use WANDA on that model from the second example, then merge it back into another model. However, that's firmly past the frontier of what has been tried, so experimentation might be messy.
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LLMs cannot find reasoning errors, but can correct them
Ah, actually reviewing that more closely I found a link to it in the acknowledgements.
https://github.com/cg123/mergekit
What are some alternatives?
skyvern - Automate browser-based workflows with LLMs and Computer Vision
Finetune_LLMs - Repo for fine-tuning Casual LLMs
lorabridge - Long-Range Data Bridge (LoRaBridge) project repository
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
flink-sql-lineage - The Lineage Analysis system for FlinkSQL supports advanced syntax such as Watermark, UDTF, CEP, Windowing TVFs, and CTAS.
LLMLingua - To speed up LLMs' inference and enhance LLM's perceive of key information, compress the prompt and KV-Cache, which achieves up to 20x compression with minimal performance loss.
spring-ai - An Application Framework for AI Engineering
task_vectors - Editing Models with Task Arithmetic
difftastic - a structural diff that understands syntax 🟥🟩
makeMoE - From scratch implementation of a sparse mixture of experts language model inspired by Andrej Karpathy's makemore :)
examples - This repository will contain examples of use cases that utilize Decodable streaming solution
Chinese-LLaMA-Alpaca - 中文LLaMA&Alpaca大语言模型+本地CPU/GPU训练部署 (Chinese LLaMA & Alpaca LLMs)