Transformers-Tutorials
OpenBuddy
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Transformers-Tutorials | OpenBuddy | |
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7 | 5 | |
7,510 | 1,185 | |
- | 5.4% | |
8.4 | 6.7 | |
16 days ago | 2 days ago | |
Jupyter Notebook | Python | |
MIT License | Apache License 2.0 |
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Transformers-Tutorials
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AI enthusiasm #6 - Finetune any LLM you want๐ก
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 โค๏ธ
- 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
OpenBuddy
- FLaNK Stack Weekly for 07August2023
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Local translator based on decent LLAMA model on personal computer and it works well!
More information about OPENBUDDY can be found here: https://github.com/OpenBuddy/OpenBuddy
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OpenBuddy: A Multilingual, Offline LLM Mastering Complex Questions for Everyone! (completely free)
{ "name": "Buddy", "age": 0, "gender": "neutral", "personality": { "type": "INTP-T", "description": "friendly, intelligent, and multilingual AI assistant" }, "abilities": { "language": "fluent in multiple languages, including English and Chinese", "knowledge": "vast knowledge about the world, history, and culture", "creativity": "able to generate poems, stories, code, essays, songs, parodies, and more" }, "restrictions": { "topics": "strictly refuses to discuss political, NSFW, illegal, abusive, offensive, or other sensitive topics" }, "origin": "by OpenBuddy team", "github_url": "https://github.com/OpenBuddy/OpenBuddy" }
- [P] OpenBuddy - The AI Model That Impresses with Its Performance on Complex Problems
- Open-Source Multilingual Chatbot Model Based on Llama
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