pipeline
layerx-community
| pipeline | layerx-community | |
|---|---|---|
| 6 | 3 | |
| 112 | 16 | |
| 2.7% | - | |
| 9.4 | 0.0 | |
| 8 days ago | about 2 years ago | |
| TypeScript | TypeScript | |
| Apache License 2.0 | GNU General Public License v3.0 or later |
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.
pipeline
-
[D] Best way to run LLMs in the cloud?
if latency is not a critical requirement, you can try serverless GPU cloud like banana.dev, pipeline.ai . These platform provide an easy to use template for deploying LLM.
-
I think we could make the website!
Assuming we choose pipeline.ai's services, we would have to pay $0.00055 per second of GPU usage. If we assume we will have 4000 users messaging 50 times a day, and every inference would take 10 seconds, we're looking at ~$33,000 every month for inference costs alone. This is a very rough estimation, as the real number of users will very likely be much higher when a website launches, and it will be greater than 50 messages per day for each user. A more realistic estimate would put us at over $100k-$150k a month.
- [P] Open source discord bot for Stable Diffusion
- Open source discord bot for Stable Diffusion
- DreamBooth Models on Serverless GPUs
- Automating API Creation in Machine Learning with Docker
layerx-community
-
Free AI assisted image labelling tool
I'm working on this open-source project. You can use it and I can help you to setup. https://github.com/LayerX-AI/layerx-community
- LayerX: A Toolset for Computer Vision Teams
-
What are the standard ways to visualise, clean and manage the large image datasets?
This is exactly missing feature in most tools. We collect so much video and image data, but you don't need all of them for labeling and then training. So data cleaning should happen before labeling. Try https://github.com/LayerX-AI/layerx-community and give us feedback. Data cleaning feature is coming in soon.
What are some alternatives?
AI-Horde - A crowdsourced distributed cluster for AI art and text generation
Mage - 🧙 The modern replacement for Airflow. Mage is an open-source data pipeline tool for transforming and integrating data. https://github.com/mage-ai/mage-ai
DarkMark - Marking up images for use with Darknet.
vscode-dvc - Machine learning experiment tracking and data versioning with DVC extension for VS Code
django-labeller - An image labelling tool for creating segmentation data sets, for Django and Flask.
xtreme1 - Xtreme1 is an all-in-one data labeling and annotation platform for multimodal data training and supports 3D LiDAR point cloud, image, and LLM.
nsfw-filter - A free, open source, and privacy-focused browser extension to block “not safe for work” content built using TypeScript and TensorFlow.js.
nfstream - NFStream: a Flexible Network Data Analysis Framework.