CX_DB8
haystack
CX_DB8 | haystack | |
---|---|---|
4 | 55 | |
222 | 13,784 | |
- | 3.6% | |
0.0 | 9.9 | |
over 1 year ago | 5 days ago | |
Python | Python | |
GNU General Public License v3.0 only | Apache License 2.0 |
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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.
CX_DB8
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Ask HN: What have you built with LLMs?
I was working on this stuff before it was cool, so in the sense of the precursor to LLMs (and sometimes supporting LLMs still) I've built many things:
1. Games you can play with word2vec or related models (could be drop in replaced with sentence transformer). It's crazy that this is 5 years old now: https://github.com/Hellisotherpeople/Language-games
2. "Constrained Text Generation Studio" - A research project I wrote when I was trying to solve LLM's inability to follow syntactic, phonetic, or semantic constraints: https://github.com/Hellisotherpeople/Constrained-Text-Genera...
3. DebateKG - A bunch of "Semantic Knowledge Graphs" built on my pet debate evidence dataset (LLM backed embeddings indexes synchronized with a graphDB and a sqlDB via txtai). Can create compelling policy debate cases https://github.com/Hellisotherpeople/DebateKG
4. My failed attempt at a good extractive summarizer. My life work is dedicated to one day solving the problems I tried to fix with this project: https://github.com/Hellisotherpeople/CX_DB8
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How critical theory is radicalizing high school debate
I really missed out on this thread despite being likely one of the most important folks to post on it (I turned my time in Policy Debate into an NLP career - see DebateSum: https://huggingface.co/datasets/Hellisotherpeople/DebateSum and CX_DB8: https://github.com/Hellisotherpeople/CX_DB8)
For those who are interested in the intersection of AI and Debate Evidence, there's a lot more work being done right now. We have a follow-up dataset to DebateSum on its way to a paper at some conference called OpenCaseList: https://huggingface.co/datasets/Yusuf5/OpenCaselist which is basically DebateSum but 40x better in every way. This is also likely the largest and best quality argument mining dataset ever gathered.
Fun anecdote, when I tried to introduce automatic extractive summarization tools to the debate community, I had parent/judge/teacher groups who were FLIPPING out about this. They were not happy at the idea of automatic debating or computer assisted debating systems.
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Copy is all you need
This has deep connections with my attempt to implement an effective queryable word-level grammatically correct extractive text summarizer (AKA: The way most people actually summarize documents) - https://github.com/Hellisotherpeople/CX_DB8
I will try to implement this with the necessary changes to actually make this work properly, where instead of generating a new answer, it simply highlights the most likely text spans.
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Haystack 1.0 – open-source NLP framework to build NLProc back end applications
Is there any path forward to make Haystack do word-level extractive summarization? e.g. like this: https://github.com/Hellisotherpeople/CX_DB8
or like this: https://huggingface.co/spaces/Hellisotherpeople/Unsupervised...
I am trying to find anything better than these two for this task. I feel like Haystack could be an option - but I am not sure.
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?
newscatcher - Programmatically collect normalized news from (almost) any website.
langchain - 🦜🔗 Build context-aware reasoning applications
reddit-thread-summarizer - A Reddit thread summarizer is a tool that generates a summary of the main points or themes discussed in a Reddit thread
langchain - ⚡ Building applications with LLMs through composability ⚡ [Moved to: https://github.com/langchain-ai/langchain]
frogbase - Transform audio-visual content into navigable knowledge.
gpt-neo - An implementation of model parallel GPT-2 and GPT-3-style models using the mesh-tensorflow library.
CNNMRF - code for paper "Combining Markov Random Fields and Convolutional Neural Networks for Image Synthesis"
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!
gpt_jailbreak_status - This is a repository that aims to provide updates on the status of jailbreaking the OpenAI GPT language model.
label-studio - Label Studio is a multi-type data labeling and annotation tool with standardized output format
joia - A ChatGPT alternative designed for team collaboration. Lightweight, privacy-friendly and open source.
jina - ☁️ Build multimodal AI applications with cloud-native stack