ColBERT
onnxruntime
| ColBERT | onnxruntime | |
|---|---|---|
| 4 | 55 | |
| 2,524 | 12,960 | |
| 7.0% | 4.4% | |
| 8.4 | 10.0 | |
| about 1 month ago | about 10 hours ago | |
| Python | C++ | |
| MIT License | MIT License |
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
-
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.
-
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
-
New free tool that uses fine-tuned BERT model to surface answers from research papers
ColBERT and successors for retrieval.
onnxruntime
-
Machine Learning with PHP
ONNX Runtime: ONNX Runtime: cross-platform, high performance ML inferencing and training accelerator
-
AI Inference now available in Supabase Edge Functions
Embedding generation uses the ONNX runtime under the hood. This is a cross-platform inferencing library that supports multiple execution providers from CPU to specialized GPUs.
-
Deep Learning in JavaScript
tfjs is dead, looking at the commit history. The standard now is to convert PyTorch to onnx, then use onnxruntime (https://github.com/microsoft/onnxruntime/tree/main/js/web) to run the model on the browsdr.
- FLaNK Stack 05 Feb 2024
-
Vcc – The Vulkan Clang Compiler
- slang[2] has the potential, but the meta programming part is not as strong as C++, existing libraries cannot be used.
The above conclusion is drawn from my work https://github.com/microsoft/onnxruntime/tree/dev/opencl, purely nightmare to work with thoes drivers and jit compilers. Hopefully Vcc can take compute shader more seriously.
[1]: https://www.circle-lang.org/
-
Oracle-samples/sd4j: Stable Diffusion pipeline in Java using ONNX Runtime
I did. It depends what you want, for an overview of how ONNX Runtime works then Microsoft have a bunch of things on https://onnxruntime.ai, but the Java content is a bit lacking on there as I've not had time to write much. Eventually I'll probably write something similar to the C# SD tutorial they have on there but for the Java API.
For writing ONNX models from Java we added an ONNX export system to Tribuo in 2022 which can be used by anything on the JVM to export ONNX models in an easier way than writing a protobuf directly. Tribuo doesn't have full coverage of the ONNX spec, but we're happy to accept PRs to expand it, otherwise it'll fill out as we need it.
- Mamba-Chat: A Chat LLM based on State Space Models
-
VectorDB: Vector Database Built by Kagi Search
What about models besides GPT? Most of the popular vector encoding models aren't using this architecture.
If you really didn't want PyTorch/Transformers, you could consider exporting your models to ONNX (https://github.com/microsoft/onnxruntime).
- ONNX runtime: Cross-platform accelerated machine learning
- Onnx Runtime: “Cross-Platform Accelerated Machine Learning”
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/
onnx - Open standard for machine learning interoperability
similarity - TensorFlow Similarity is a python package focused on making similarity learning quick and easy.
onnx-tensorrt - ONNX-TensorRT: TensorRT backend for ONNX
elasticsearch-learning-to-rank - Plugin to integrate Learning to Rank (aka machine learning for better relevance) with Elasticsearch
onnx-simplifier - Simplify your onnx model
Milvus - A cloud-native vector database, storage for next generation AI applications
ONNX-YOLOv7-Object-Detection - Python scripts performing object detection using the YOLOv7 model in ONNX.
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.
onnx-tensorflow - Tensorflow Backend for ONNX
awesome-semantic-search - A curated list of awesome resources related to Semantic Search🔎 and Semantic Similarity tasks.
MLflow - Open source platform for the machine learning lifecycle