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Top 10 Jupyter Notebook Onnx Projects
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silero-models
Silero Models: pre-trained speech-to-text, text-to-speech and text-enhancement models made embarrassingly simple
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InfluxDB
Power Real-Time Data Analytics at Scale. Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.
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x-stable-diffusion
Real-time inference for Stable Diffusion - 0.88s latency. Covers AITemplate, nvFuser, TensorRT, FlashAttention. Join our Discord communty: https://discord.com/invite/TgHXuSJEk6
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WorkOS
The modern identity platform for B2B SaaS. The APIs are flexible and easy-to-use, supporting authentication, user identity, and complex enterprise features like SSO and SCIM provisioning.
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InteractiveAnnotation
Interactive Annotation using Segment Anything for fast and accurate segmentation
Project mention: AMD Accelerates AI Adoption on Windows 11 With New Developer Tools for Ryzen AI | /r/AMD_Stock | 2023-05-23Uh, maybe they didn't feel the need to look. I already pointed you to the ONNX project. Here are some ONNX-based. These are just the ones being shared with the community. The limit of AMD's responsibility is writing the low-level libraries to support ONNX.
Project mention: Weird A.I. Yankovic, a cursed deep dive into the world of voice cloning | news.ycombinator.com | 2023-10-02I doubt it's currently actually "the best open source text to speech", but the answer I came up with when throwing a couple of hours at the problem some months ago was "Silero" [0, 1].
Following the "standalone" guide [2], it was pretty trivial to make the model render my sample text in about 100 English "voices" (many of which were similar to each other, and in varying quality). Sampling those, I got about 10 that were pretty "good". And maybe 6 that were the "best ones" (pretty natural, not annoying to listen to).
IIRC the license was free for noncommercial use only. I'm not sure exactly "how open source" they are, but it was simple to install the dependencies and write the basic Python to try it out; I had to write a for loop to try all the voices like I wanted. I ended using something else for the project for other reasons, but this could still be fairly good backup option for some use cases IMO.
[0] https://github.com/snakers4/silero-models#text-to-speech
The easiest way to transform the downloaded TensorFlow model to an ONNX model is to use the tool tf2onnx from https://github.com/onnx/tensorflow-onnx
Project mention: Boost 🚀 your (instance) segmentation labeling using the trainYOLO platform. | /r/computervision | 2023-04-20Really cool here is also opensource implementation of instance segmentation using segement anything https://github.com/Asad-Ismail/InteractiveAnnotation
Jupyter Notebook Onnx related posts
- Which models can be converted to ONNX?
- Need Help With Darknet YOLOv4-Tiny Model In Unity Barracuda
- Need Help Converting Darknet Yolov4-tiny Model to ONNX
- Auto Annotation using ONNX and YOLOv7 model (Object Detection)
- [Tutorial] "Fine Tuning" Stable Diffusion using only 5 Images Using Textual Inversion.
- Can you inference a .tflite model file using Pytorch mobile?
- How to identify identical frames that are not technically duplicates? Ie if I am taking a video of a car, it stops for 1 minute (and within that minute nothing changes visually), and then drives away. How would I remove all but 1 of the frames when it is stopped?
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A note from our sponsor - SaaSHub
www.saashub.com | 19 Apr 2024
Index
What are some of the best open-source Onnx projects in Jupyter Notebook? This list will help you:
Project | Stars | |
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1 | models | 7,135 |
2 | silero-models | 4,534 |
3 | tensorflow-onnx | 2,210 |
4 | x-stable-diffusion | 548 |
5 | w2v2-how-to | 398 |
6 | optimum-intel | 317 |
7 | browser-ml-inference | 294 |
8 | Deepstream | 82 |
9 | redisai-examples | 54 |
10 | InteractiveAnnotation | 20 |