tldr-transformers
haystack
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| tldr-transformers | haystack | |
|---|---|---|
| 4 | 54 | |
| 167 | 13,486 | |
| - | 4.8% | |
| 0.0 | 9.9 | |
| over 1 year ago | 7 days ago | |
| 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.
tldr-transformers
- Show HN: The “tl;dr” of Recent Transformer Papers
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Show HN: Tl;Dr” on Transformers Papers
With the explosion in research on all things transformers, it seemed there was a need to have a single table to distill the "tl;dr" of each paper's contributions relative to each other. Here is what I got so far: https://github.com/will-thompson-k/tldr-transformers . Would love feedback - and feel free to contribute too :)
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[P] NLP "tl;dr" Notes on Transformers
In any case, I'm liking the first glance so far. I'd just transpose the summary tables so they wouldn't get so tightly squeezed: https://github.com/will-thompson-k/tldr-transformers/blob/main/notes/bart.md
With the explosion in work on all things transformers, I felt the need to keep a single table of the "tl;dr" of various papers to distill their main takeaways: https://github.com/will-thompson-k/tldr-transformers . Would love feedback!
haystack
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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
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Langchain Is Pointless
there is an alternative that is production-grade - deepset haystack https://haystack.deepset.ai/
p.s. i am contributor so there could be bias
What are some alternatives?
NLP-progress - Repository to track the progress in Natural Language Processing (NLP), including the datasets and the current state-of-the-art for the most common NLP tasks.
langchain - 🦜🔗 Build context-aware reasoning applications
FARM - :house_with_garden: Fast & easy transfer learning for NLP. Harvesting language models for the industry. Focus on Question Answering.
langchain - ⚡ Building applications with LLMs through composability ⚡ [Moved to: https://github.com/langchain-ai/langchain]
lemmatization-lists - Machine-readable lists of lemma-token pairs in 23 languages.
gpt-neo - An implementation of model parallel GPT-2 and GPT-3-style models using the mesh-tensorflow library.
azure-sql-db-openai - Samples on how to use Azure SQL database with Azure OpenAI
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!
long-range-arena - Long Range Arena for Benchmarking Efficient Transformers
label-studio - Label Studio is a multi-type data labeling and annotation tool with standardized output format
transformers-convert
jina - ☁️ Build multimodal AI applications with cloud-native stack