dstack
spark-nlp-workshop
| dstack | spark-nlp-workshop | |
|---|---|---|
| 17 | 16 | |
| 1,136 | 1,006 | |
| 4.3% | 0.9% | |
| 9.8 | 9.6 | |
| 6 days ago | 8 days ago | |
| Python | Jupyter Notebook | |
| Mozilla Public 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.
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.
dstack
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Pyinfra: Automate Infrastructure Using Python
We build a similar tool except we focus on AI workloads. Also support on-prem clusters now in addition to GPU clouds. https://github.com/dstackai/dstack
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Show HN: Open-source alternative to HashiCorp/IBM Vault
Not exactly this, but something related. At https://github.com/dstackai/dstack, we build an alternative to K8S for AI infra.
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Ask HN: How does deploying a fine-tuned model work
You can use https://github.com/dstackai/dstack to deploy your model to the most affordable GPU clouds. It supports auto-scaling and other features.
Disclaimer: I’m the creator of dstack.
- FLaNK Stack Weekly 19 Feb 2024
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Show HN: I Built an Open Source API with Insanely Fast Whisper and Fly GPUs
Great job on the project! It looks fantastic. Thanks to your post, I discovered Fly's GPUs. We are currently developing a platform called https://github.com/dstackai/dstack that enables users to run any model on any cloud. I am curious if it would be possible to add support for Fly.io as well. If you are interested in collaborating on this, please let me know!
- Show HN: Dstack – an open-source engine for running GPU workloads
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[P] I built a tool to compare cloud GPUs. How should I improve it?
I also noticed that the creator of this app, dstack, is affiliated with Tensordock, the top results for most if not all queries. If that's the case, perhaps a direct link to the cheapest machine could be provided? I haven't used Tensordock, so I don't know if this is mechanically possible.
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Running dev environments and ML tasks cost-effectively in any cloud
Here's the repository with all the important links, including documentation, examples, and more: https://github.com/dstackai/dstack
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Dstack Hub
Hey everyone, I'm happy to release dstack Hub, an open-source tool that helps teams manage their ML workflows more effectively without vendor lock-in.
dstack Hub extend dstack [1] with workflow scheduling capabilities and user management. Here's how it works: run dstack Hub via Docker, use its UI to configure projects and cloud credentials, then pass the URL and personal token to the dstack CLI. Now, you can run workflows through the CLI and Hub will orchestrate them in the cloud on your behalf.
This is a beta release and we plan to continuously improve it. We'd love to hear your feedback and answer any questions!
[1] https://github.com/dstackai/dstack
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Running Stable Diffusion Locally & in Cloud with Diffusers & dstack
To help you overcome this challenge, we have written an article to guide you through the simple steps of using both diffusers and dstack to generate images from prompts, both locally and in the cloud, using a simple example.
spark-nlp-workshop
- FLaNK Stack Weekly 19 Feb 2024
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Spark-NLP 4.1.0 Released: Vision Transformer (ViT) is here! The very first Computer Vision pipeline for the state-of-the-art Image Classification task, AWS Graviton/ARM64 support, new EMR & Databricks support, 1000+ state-of-the-art models, and more!
You can visit Spark NLP Workshop for 100+ examples
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Spark-NLP 4.0.0 🚀: New modern extractive Question answering (QA) annotators for ALBERT, BERT, DistilBERT, DeBERTa, RoBERTa, Longformer, and XLM-RoBERTa, official support for Apple silicon M1, support oneDNN to improve CPU up to 97%, improved transformers on GPU up to +700%, 1000+ SOTA models
I submitted a pull request here: https://github.com/JohnSnowLabs/spark-nlp-workshop/pull/552 that I think addresses both of those.
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How AI is used for mental health therapy
In SnowLab’s implementation, for example, they wrote a search function called get_clinical_entities that finds all mentions of medications for 100 patients, as well as specifications, if any, about the quantity and frequency the medication is consumed. The location of the sentence in the overall piece is also recorded, to locate the information easier.
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John Snow Labs Spark-NLP 3.4.0: New OpenAI GPT-2, new ALBERT, XLNet, RoBERTa, XLM-RoBERTa, and Longformer for Sequence Classification, support for Spark 3.2, new distributed Word2Vec, extend support to more Databricks & EMR runtimes, new state-of-the-art transformer models, bug fixes, and lots more!
There are so many examples here for Python users (I would start from tutorials/Certificate_Trainings): https://github.com/JohnSnowLabs/spark-nlp-workshop
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John Snow Labs Spark-NLP 3.1.0: Over 2600+ new models and pipelines in 200+ languages, new DistilBERT, RoBERTa, and XLM-RoBERTa transformers, support for external Transformers, and lots more!
Spark NLP Workshop notebooks
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Release John Snow Labs Spark-NLP 2.7.0: New T5 and MarianMT seq2seq transformers, detect up to 375 languages, word segmentation, over 720+ models and pipelines, support for 192+ languages, and many more! · JohnSnowLabs/spark-nlp
Spark NLP training certification notebooks for Google Colab and Databricks
Spark NLP training certification notebooks for Google Colab and Databricks
Spark NLP training certification notebooks for Google Colab and Databricks
Spark NLP training certification notebooks for Google Colab and Databricks
What are some alternatives?
msdocs-python-django-azure-container-apps - Python web app using Django that can be deployed to Azure Container Apps.
spark-nlp - State of the Art Natural Language Processing
dstack-examples - A collection of examples demonstrating how to use dstack
spark-nlp-display - A library for the simple visualization of different types of Spark NLP annotations.
zenml - ZenML 🙏: Build portable, production-ready MLOps pipelines. https://zenml.io.
proton - A streaming SQL engine, a fast and lightweight alternative to ksqlDB and Apache Flink, 🚀 powered by ClickHouse.
flyte - Scalable and flexible workflow orchestration platform that seamlessly unifies data, ML and analytics stacks.
TensorRT-LLM - TensorRT-LLM provides users with an easy-to-use Python API to define Large Language Models (LLMs) and build TensorRT engines that contain state-of-the-art optimizations to perform inference efficiently on NVIDIA GPUs. TensorRT-LLM also contains components to create Python and C++ runtimes that execute those TensorRT engines.
lambdapi - Serverless runtime environment tailored for code produced by LLMs. Automatic API generation from your code, support for multiple programming languages, and integrated file and database storage solutions.
magika - Detect file content types with deep learning
metaflow - :rocket: Build and manage real-life ML, AI, and data science projects with ease!
openvino-plugins-ai-audacity - A set of AI-enabled effects, generators, and analyzers for Audacity®.