autocards
haystack
| autocards | haystack | |
|---|---|---|
| 9 | 55 | |
| 116 | 13,711 | |
| - | 3.1% | |
| 0.0 | 9.9 | |
| almost 2 years ago | 2 days ago | |
| Python | Python | |
| MIT License | Apache License 2.0 |
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.
autocards
- Autocards
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Automatically generating of anki decks with artificial intelligence from pdfs, docs, and txt
Are you familiar with autocards? https://github.com/paulbricman/autocards it also uses a language ai (gpt) for making anki cards automatically
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Any automatic card creator?
More information for the content you're wishing to create cards for would be helpful to include. I've been toying with an AI project that was posted a while back called autocards which interprets written text and then generates questions. It isn't perfect, but provides a nice base to build on for learning new material. Copying text from Wikipedia articles or textbooks has produced some useful cards, but you still have to edit grammar occasionally and it doesn't work super great for subjects with irregular sentence structures (i.e. chemistry texts that use long notation of molecules including lots of dashes and commas)
- Gaguing interest/ seeking help for a long term implementation of Anki along side NLP language models to revolutionize second language aquisition
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Does anyone get frustrated with making cards?
Wow, seems nice. Have you tried this? Here's a much more user-friendly link for that, with actual examples: https://paulbricman.com/docs/tools/autocards/.
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Automatically generate flashcards from books, articles, and papers using AI
Sounds like a nice possible option, ignore_references as an option of the consume functions or something. Thanks for the idea! Added here.
haystack
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Haystack DB – 10x faster than FAISS with binary embeddings by default
I was confused for a bit but there is no relation to https://haystack.deepset.ai/
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Release Radar • March 2024 Edition
View on GitHub
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First 15 Open Source Advent projects
4. Haystack by Deepset | Github | tutorial
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Generative AI Frameworks and Tools Every Developer Should Know!
Haystack can be classified as an end-to-end framework for building applications powered by various NLP technologies, including but not limited to generative AI. While it doesn't directly focus on building generative models from scratch, it provides a robust platform for:
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Best way to programmatically extract data from a set of .pdf files?
But if you want an API that you can use to develop your own flow, Haystack from Deepset could be worth a look.
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Which LLM framework(s) do you use in production and why?
Haystack for production. We cannot afford breaking changes in our production apps. Its stable, documentation is excellent and did I mention its' STABLE!??
- Overview: AI Assembly Architectures
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Llama2 and Haystack on Colab
I recently conducted some experiments with Llama2 and Haystack (https://github.com/deepset-ai/haystack), the NLP/LLM framework.
The notebook can be helpful for those trying to load Llama2 on Colab.
1) Installed Transformers from the main branch (and other libraries)
- Build with LLMs for production with Haystack – has 10k stars on GitHub
- Show HN: Haystack – Production-Ready LLM Framework
What are some alternatives?
speed-focus-mode - Speed Focus Mode add-on for Anki
langchain - 🦜🔗 Build context-aware reasoning applications
AnnA_Anki_neuronal_Appendix - Using machine learning on your anki collection to enhance the scheduling via semantic clustering and semantic similarity
langchain - ⚡ Building applications with LLMs through composability ⚡ [Moved to: https://github.com/langchain-ai/langchain]
incremental-reading - Anki add-on providing incremental reading features
gpt-neo - An implementation of model parallel GPT-2 and GPT-3-style models using the mesh-tensorflow library.
LibreLingo - 🐢 🌎 📚 a community-owned language-learning platform
BentoML - The most flexible way to serve AI/ML models in production - Build Model Inference Service, LLM APIs, Inference Graph/Pipelines, Compound AI systems, Multi-Modal, RAG as a Service, and more!
mnemocards - In addition to helping you memorise, this code helps you do other things that I don't remember...
label-studio - Label Studio is a multi-type data labeling and annotation tool with standardized output format
autoanki
jina - ☁️ Build multimodal AI applications with cloud-native stack