byt5-geotagging
haystack
byt5-geotagging | haystack | |
---|---|---|
30 | 55 | |
155 | 13,883 | |
0.6% | 4.3% | |
6.7 | 9.9 | |
3 months ago | about 16 hours 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.
byt5-geotagging
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Locating discussions about Donald Trump charges by using NLP
They also have a website from what I saw https://www.yachay.ai/ and I visited their Twitter.
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[OC] We tracked mentions of OpenAI, Bing, and Bard across social media to find out who's the most talked about in Silicon Valley
Source: social media Tool: geolocation models + folium
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We tracked mentions of OpenAI, Bing, and Bard across social media to find out who's the most talked about in Silicon Valley
We used social media data and geolocation models to find posts about OpenAI, Bing, and Bard in the Silicon Valley and San Francisco Bay Area for the last two weeks to see which one received the most mentions.
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[OC] Heat map of Twitter mentions of "Rihanna" and "Riri" before and after the Super Bowl. Made with folium + our text-to-location models.
We've open-sourced the infrastructure and data to our character-level transformer-based models here
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We used text-to-location models to locate Twitter mentions of "Rihanna" and "Riri" during the Super Bowl
Oh of course it's more than that - check us out on github!
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We used text-to-location models to find Twitter mentions of "Rihanna" and "Riri" during the Super Bowl - Github in comments
Our Github with open-source text-to-location models
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We used deep learning models to map a heat map of Twitter mentions of "Rihanna" and "Riri" before and after the Super Bowl
Source: Text-to-location models Visualization Tool: Folium
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We applied ML models to find Twitter mentions of "Rihanna" and "Riri" during the Super Bowl
We used ML models to locate tweets about Rihanna and then used folium to visualize the data.
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We made a map showing what each US state "loves" with open-source text-to-location models
As a member of /r/OSINT you could have found it yourself π https://github.com/1712n/yachay-public
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Hey guys! We launched a Kaggle competition for finding accurate coordinates from text alone ππ
Check out our website, too
haystack
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Haystack DB β 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 β’ 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 ToolsΒ 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 β has 10k stars on GitHub
- Show HN: Haystack β Production-Ready LLM Framework
What are some alternatives?
langchain - π¦π Build context-aware reasoning applications
langchain - β‘ Building applications with LLMs through composability β‘ [Moved to: https://github.com/langchain-ai/langchain]
gpt-neo - An implementation of model parallel GPT-2 and GPT-3-style models using the mesh-tensorflow library.
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!
label-studio - Label Studio is a multi-type data labeling and annotation tool with standardized output format
jina - βοΈ Build multimodal AI applications with cloud-native stack
BERT-pytorch - Google AI 2018 BERT pytorch implementation
BERT-NER - Pytorch-Named-Entity-Recognition-with-BERT
gpt-neox - An implementation of model parallel autoregressive transformers on GPUs, based on the Megatron and DeepSpeed libraries
jina-financial-qa-search
scibert - A BERT model for scientific text.
Questgen.ai - Question generation using state-of-the-art Natural Language Processing algorithms