ColBERT
openvino
| ColBERT | openvino | |
|---|---|---|
| 4 | 17 | |
| 2,524 | 6,028 | |
| 7.0% | 4.9% | |
| 8.4 | 10.0 | |
| about 1 month ago | 5 days ago | |
| Python | C++ | |
| 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.
ColBERT
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Why Vector Compression Matters
I’ll conclude by explaining how vector compression relates to ColBERT, a higher-level technique that Astra DB customers are starting to use successfully.
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How ColBERT Helps Developers Overcome the Limits of Retrieval-Augmented Generation
ColBERT is a new way of scoring passage relevance using a BERT language model that substantially solves the problems with DPR. This diagram from the first ColBERT paper shows why it’s so exciting:
- FLaNK Stack 05 Feb 2024
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New free tool that uses fine-tuned BERT model to surface answers from research papers
ColBERT and successors for retrieval.
openvino
- FLaNK Stack 05 Feb 2024
- QUIK is a method for quantizing LLM post-training weights to 4 bit precision
- Intel OpenVINO 2023.1.0 released
- Intel OpenVINO 2023.1.0 released, open-source toolkit for optimizing and deploying AI inference
- OpenVINO 2023.1.0 released
- [N] Intel OpenVINO 2023.1.0 released, open-source toolkit for optimizing and deploying AI inference
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Powering Anomaly Detection for Industry 4.0
Anomalib is an open-source deep learning library developed by Intel that makes it easy to benchmark different anomaly detection algorithms on both public and custom datasets, all by simply modifying a config file. As the largest public collection of anomaly detection algorithms and datasets, it has a strong focus on image-based anomaly detection. It’s a comprehensive, end-to-end solution that includes cutting-edge algorithms, relevant evaluation methods, prediction visualizations, hyperparameter optimization, and inference deployment code with Intel’s OpenVINO Toolkit.
What are some alternatives?
qdrant - Qdrant - High-performance, massive-scale Vector Database for the next generation of AI. Also available in the cloud https://cloud.qdrant.io/
TensorRT - NVIDIA® TensorRT™ is an SDK for high-performance deep learning inference on NVIDIA GPUs. This repository contains the open source components of TensorRT.
similarity - TensorFlow Similarity is a python package focused on making similarity learning quick and easy.
deepsparse - Sparsity-aware deep learning inference runtime for CPUs
elasticsearch-learning-to-rank - Plugin to integrate Learning to Rank (aka machine learning for better relevance) with Elasticsearch
mediapipe - Cross-platform, customizable ML solutions for live and streaming media.
Milvus - A cloud-native vector database, storage for next generation AI applications
stable-diffusion - Go to lstein/stable-diffusion for all the best stuff and a stable release. This repository is my testing ground and it's very likely that I've done something that will break it.
haystack - :mag: LLM orchestration framework to build customizable, production-ready LLM applications. Connect components (models, vector DBs, file converters) to pipelines or agents that can interact with your data. With advanced retrieval methods, it's best suited for building RAG, question answering, semantic search or conversational agent chatbots.
neural-compressor - SOTA low-bit LLM quantization (INT8/FP8/INT4/FP4/NF4) & sparsity; leading model compression techniques on TensorFlow, PyTorch, and ONNX Runtime
awesome-semantic-search - A curated list of awesome resources related to Semantic Search🔎 and Semantic Similarity tasks.
nebuly - The user analytics platform for LLMs