EverythingApacheNiFi
pytorch-image-models
EverythingApacheNiFi | pytorch-image-models | |
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4 | 35 | |
90 | 29,903 | |
- | 1.7% | |
5.8 | 9.4 | |
7 months ago | 6 days ago | |
Python | ||
Apache License 2.0 | Apache License 2.0 |
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EverythingApacheNiFi
- FLaNK Stack Weekly for 07August2023
- Apache Nifi - Best courses?
- NiFi on Cloudera Data Platform Upgrade - April 2021
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Simple Change Data Capture (CDC) with SQL Selects via Apache NiFi (FLaNK)
https://github.com/tspannhw/EverythingApacheNiFi#etl--elt--cdc--load--ingest
pytorch-image-models
- FLaNK AI Weekly 18 March 2024
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[D] Hugging face and Timm
I am a PyTorch user I work in CV, I usually use the PyTorch models. However, I see people use timm in research papers to train their models I don't understand what it is timm is it a new framework like PyTorch? Further, when I click https://pypi.org/project/timm/ homepage it takes me to hugging face GitHub https://github.com/huggingface/pytorch-image-models is there any connection between timm and hugging face many of my friends use hugging face but I also don't know about hugging face I use simple PyTorch and torchvision.models.
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FLaNK Stack Weekly for 07August2023
https://github.com/huggingface/pytorch-image-models https://huggingface.co/docs/timm/index
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[R] Nvidia RTX 4090 ML benchmarks. Under QEMU/KVM. Image + Transformers. FP16/FP32.
pytorch-image-models
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Inference on resent, cant work out the problem?
additionally, you might find the timm library handy for this sort of work.
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Swin Transformer: Hierarchical Vision Transformer Using Shifted Windows
This is still being pursued. Ross Wightmann's timm[0,1] package (now on Hugging Face) has done a lot of this. There's also a V2 of ConvNext[2]. Ross does write about this a lot on Twitter fwiw. I should also mention that there are still many transformer based networks that still beat convs. So there probably won't be a resurgence in convs until someone can show that there's a really strong reason for them. They have some advantages but they also might not be flexible enough for the long range tasks in segmentation and detection. But maybe they are.
FAIR definitely did great work with ConvNext, and I do hope to see more. There always needs to be people pushing unpopular paradigms.
[0] https://github.com/huggingface/pytorch-image-models
[1] https://arxiv.org/abs/2110.00476
[2] https://arxiv.org/abs/2301.00808
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Problems with Learning Rate Finder in Pytorch Lightning
I am doing Binary classification with a pre-trained EfficientNet tf_efficientnet_l2. I froze all weights during training and replaced the classifier with a custom trainable one that looks like:
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PyTorch at the Edge: Deploying Over 964 TIMM Models on Android with TorchScript and Flutter
In this post, Iām going to show you how you can pick from over 900+ SOTA models on TIMM, train them using best practices with Fastai, and deploy them on Android using Flutter.
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ImageNet Advise
The other thing is, try to find tricks to speed up your experiments (if not having done so already). The most obvious are mixed precision training, have your model train on a lower resolution input first and then increase the resolution later in the training, stochastic depth, and a bunch more stuffs. Look for implementations in https://github.com/rwightman/pytorch-image-models .
- Doubt about transformers
What are some alternatives?
examples - Analyze the unstructured data with Towhee, such as reverse image search, reverse video search, audio classification, question and answer systems, molecular search, etc.
yolov5 - YOLOv5 š in PyTorch > ONNX > CoreML > TFLite
Qwen-7B - The official repo of Qwen (éä¹åé®) chat & pretrained large language model proposed by Alibaba Cloud. [Moved to: https://github.com/QwenLM/Qwen]
mmdetection - OpenMMLab Detection Toolbox and Benchmark
CallCMLModel - An example on calling models deployed in CML
detectron2 - Detectron2 is a platform for object detection, segmentation and other visual recognition tasks.
llama2_aided_tesseract - Enhance Tesseract OCR output for scanned PDFs by applying Large Language Model (LLM) corrections, complete with options for text validation and hallucination filtering.
mmcv - OpenMMLab Computer Vision Foundation
ToolBench - [ICLR'24 spotlight] An open platform for training, serving, and evaluating large language model for tool learning.
segmentation_models.pytorch - Segmentation models with pretrained backbones. PyTorch.
anomalib - An anomaly detection library comprising state-of-the-art algorithms and features such as experiment management, hyper-parameter optimization, and edge inference.
yolact - A simple, fully convolutional model for real-time instance segmentation.