instructor-embedding
haystack
instructor-embedding | haystack | |
---|---|---|
4 | 55 | |
1,703 | 13,711 | |
3.1% | 3.1% | |
5.9 | 9.9 | |
10 days ago | 2 days ago | |
Python | Python | |
Apache License 2.0 | Apache License 2.0 |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
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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.
instructor-embedding
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My experience on starting with fine tuning LLMs with custom data
If you li embeddings and vector DB, you should look into this: https://github.com/HKUNLP/instructor-embedding
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Build Personal ChatGPT Using Your Data
If you look at a embeddings leaderboard [1], one of the top competitors called InstructorXL [2] is just a pip install away. It's neck and neck with Ada v2 except for a shorter input length and half the dimensions, with the added benefit that you'll always have the model available.
Most of the other options just work with the transformers library.
[1] https://huggingface.co/spaces/mteb/leaderboard
[2] https://github.com/HKUNLP/instructor-embedding
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I've made a customisable SMS personal assistant which has infinite and persistent semantic memory.
Use instructor-embedding to to make it 100% local and even maybe quick relationship lookup (embed relationship info with sentiment analysis instruction)
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Whisper Transcription Formatting
First.I believe having srt subtitles as whisper result would be better.Essentially you don't need just a list of words like YouTube does.You need something more structured.I don't remember what whisper outputs so I might be wrong.There is whisperx for that as example. And then maybe use gpt index over it.Or something like instructor model That can work.
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?
h2ogpt - Private chat with local GPT with document, images, video, etc. 100% private, Apache 2.0. Supports oLLaMa, Mixtral, llama.cpp, and more. Demo: https://gpt.h2o.ai/ https://codellama.h2o.ai/
langchain - 🦜🔗 Build context-aware reasoning applications
openai-cookbook - Examples and guides for using the OpenAI API
langchain - ⚡ Building applications with LLMs through composability ⚡ [Moved to: https://github.com/langchain-ai/langchain]
Nuggt - An Autonomous LLM Agent that runs on Wizcoder-15B
gpt-neo - An implementation of model parallel GPT-2 and GPT-3-style models using the mesh-tensorflow library.
vlite - fast vector database made in numpy
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!
easydiffusion - Easiest 1-click way to create beautiful artwork on your PC using AI, with no tech knowledge. Provides a browser UI for generating images from text prompts and images. Just enter your text prompt, and see the generated image.
label-studio - Label Studio is a multi-type data labeling and annotation tool with standardized output format
lit-gpt - Hackable implementation of state-of-the-art open-source LLMs based on nanoGPT. Supports flash attention, 4-bit and 8-bit quantization, LoRA and LLaMA-Adapter fine-tuning, pre-training. Apache 2.0-licensed. [Moved to: https://github.com/Lightning-AI/litgpt]
jina - ☁️ Build multimodal AI applications with cloud-native stack