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How to use LLMs locally with ollama and Python

Towards AI

This article will walk you through using ollama, a command line tool that allows you to download, explore and use Large Language Models (LLM) on your local PC, whether Windows, Mac or Linux, with GPU support. Join thousands of data leaders on the AI newsletter. From research to projects and ideas.

Python 99
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Towards Autonomous Software Development: The SWE-agent Revolution

Marktechpost

It operates by outputting thoughts and commands and then receiving feedback from command execution using the ReAct environment. SWE-agent revolutionizes LM interaction in software engineering by providing a tailored ACI for navigating, editing, and executing code commands. If you like our work, you will love our newsletter.

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MaRDIFlow: Automating Metadata Abstraction for Enhanced Reproducibility in Computational Workflows

Marktechpost

The working prototype, accessible via command line, enables execution, documentation, and provenance maintenance for computer-based experiments, facilitating reproducibility and replication. If you like our work, you will love our newsletter. All credit for this research goes to the researchers of this project.

Metadata 102
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How to Fine-tune EasyOCR to achieve better OCR performance

Towards AI

Run the commands below one line at a time: pip install firepip install lmdbpip install opencv-pythonpip install natsortpip install nltk You also need to install PyTorch from this website (choose your specifications and copy the pip install command, see the command below that I used for my specifications).

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Getting Used to Docker for Machine Learning

Flipboard

In today’s blog, we will look at how we can create and build our own containers with a Dockerfile , followed by the most commonly used Docker commands and the concepts behind them. It allows us to start API development within a few lines of simple Python code. Let’s look at the Dockerfile now and go line by line.

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Trending AI GitHub Repos: Week of November 13, 2023

ODSC - Open Data Science

It has support for 600+ command line tools and is available for Windows, Linux, and MacOS. This means that you can use it to get autocomplete suggestions for commands, options, and arguments when you are typing in a shell. This can be a great time-saver, especially if you are working with a lot of complex commands.

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How To Create Powerful Embeddings From Topology Information In Graphs

Towards AI

Motivation· Installing the required packages:· Assumptions· Deepwalk/Node2vec· GNNs· LINE· Apply clustering to the embeddings· Conclusion· References Using a graph can be a good way of encoding lots of information. Join thousands of data leaders on the AI newsletter. ChatGPT, OpenAI, 30 Jan. g/g-2fkFE8rbu-dall-e.

OpenAI 99