Language-Translation-with-Fragment-Shaders
haystack
| Language-Translation-with-Fragment-Shaders | haystack | |
|---|---|---|
| 1 | 55 | |
| 89 | 13,633 | |
| - | 2.5% | |
| 1.8 | 9.9 | |
| almost 2 years ago | 6 days ago | |
| ShaderLab | Python | |
| MIT License | Apache License 2.0 |
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Language-Translation-with-Fragment-Shaders
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I made a Japanese/English translator with just fragment shaders for VR
It's just for educational purposes on how ML works, not very fast or practical. The entire thing's here for free https://github.com/SCRN-VRC/Language-Translation-with-Fragment-Shaders
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?
Anime-Speed-Lines - Post-processing effect to procedurally generate a anime/manga-style vignette of lines typically used to portray speed or surprise.
langchain - 🦜🔗 Build context-aware reasoning applications
SimpNet-Deep-Learning-in-a-Shader - A trainable convolutional neural network inside a fragment shader
langchain - ⚡ Building applications with LLMs through composability ⚡ [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 - ☁️ 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 DeepSpeed library.
jina-financial-qa-search