Transformers-Tutorials
yyjson
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| Transformers-Tutorials | yyjson | |
|---|---|---|
| 7 | 5 | |
| 7,510 | 2,831 | |
| - | - | |
| 8.4 | 7.4 | |
| 16 days ago | 20 days ago | |
| Jupyter Notebook | C | |
| MIT License | MIT License |
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Transformers-Tutorials
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AI enthusiasm #6 - Finetune any LLM you want💡
Most of this tutorial is based on Hugging Face course about Transformers and on Niels Rogge's Transformers tutorials: make sure to check their work and give them a star on GitHub, if you please ❤️
- FLaNK Stack Weekly for 07August2023
- How to annotate compound words to build NER models?
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[discussion] Anybody Working with VITMAE?
I'm pretraining on 850K grayscale spectrograms of birdsongs. I'm on epoch 400 out of 800 and the loss has declined from about 1.2 to 0.7. I don't really have a sense of what is "good enough" and I guess the only way I can judge is by looking at the reconstruction. I'm doing that using this notebook as a guide and right now it's doing quite badly.
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[D] NLP has HuggingFace, what does Computer Vision have?
More tutorials can be found at https://github.com/NielsRogge/Transformers-Tutorials.
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[Discussion] Information Extraction with LayoutLMv2
Ive been looking for an off the shelf encoder-decoder document understanding model for key information extraction. I found a great Huggingface implementation with concise notebook examples. However, the token classification model outputs a list of token labels corresponding bounding boxes for the token, but, not the text contained within the labeled bounding boxes themselves. Am I missing something? LayoutLMv2 describes itself as being capable of information extraction but without extracting the text I feel like it's fallen short of that ambition.
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[Project] Deepmind's Perceiver IO available through Hugging Face
Example Notebooks
yyjson
- FLaNK Stack Weekly for 07August2023
- yyjson: A high performance C JSON library
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Show HN: Up to 100x Faster FastAPI with simdjson and io_uring on Linux 5.19
How does yyjson[0] compare to simdjson? Their benchmarks suggest it could be a positive.
[0] https://github.com/ibireme/yyjson
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Why is my program segfaulting?
Also I am using these libraries: JSON: https://github.com/ibireme/yyjson Networking: https://curl.se/libcurl/
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How to parse JSON in C ?
If you need speed, by far yyjson. But it sounds like you probably don't need speed, so the other suggestions are likely better.
What are some alternatives?
nn - 🧑🏫 60 Implementations/tutorials of deep learning papers with side-by-side notes 📝; including transformers (original, xl, switch, feedback, vit, ...), optimizers (adam, adabelief, sophia, ...), gans(cyclegan, stylegan2, ...), 🎮 reinforcement learning (ppo, dqn), capsnet, distillation, ... 🧠
json-c - https://github.com/json-c/json-c is the official code repository for json-c. See the wiki for release tarballs for download. API docs at http://json-c.github.io/json-c/
gorilla-cli - LLMs for your CLI
cJSON - Ultralightweight JSON parser in ANSI C
pytorch-image-models - PyTorch image models, scripts, pretrained weights -- ResNet, ResNeXT, EfficientNet, NFNet, Vision Transformer (ViT), MobileNet-V3/V2, RegNet, DPN, CSPNet, Swin Transformer, MaxViT, CoAtNet, ConvNeXt, and more
JSMN - Jsmn is a world fastest JSON parser/tokenizer. This is the official repo replacing the old one at Bitbucket
notebooks - Notebooks using the Hugging Face libraries 🤗
parson - Lightweight JSON library written in C.
adaptnlp - An easy to use Natural Language Processing library and framework for predicting, training, fine-tuning, and serving up state-of-the-art NLP models.
ultrajson - Ultra fast JSON decoder and encoder written in C with Python bindings
OpenBuddy - Open Multilingual Chatbot for Everyone