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huggingface/llm-swarm

0
View on GitHub↗
288 stars·28 forks·Python·MIT·11 views

Llm Swarm

Manage scalable open LLM inference endpoints in Slurm clusters

Features

  • Data Processing - Framework for generating large synthetic datasets.
  • Data Processing Tools - Framework for generating large-scale synthetic training datasets.

Star history

Star history chart for huggingface/llm-swarmStar history chart for huggingface/llm-swarm

How this analysis was created: This summary and feature list were written by an AI model that read the project's README and public documentation pages. Each feature links to the documentation it came from; stars, license and language come straight from the GitHub API. The model does not read the source code, and the analysis is refreshed when the project is re-analysed. Learn more on our About page.

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Frequently asked questions

What does huggingface/llm-swarm do?

Manage scalable open LLM inference endpoints in Slurm clusters

What are the main features of huggingface/llm-swarm?

The main features of huggingface/llm-swarm are: Data Processing, Data Processing Tools.

What are some open-source alternatives to huggingface/llm-swarm?

Open-source alternatives to huggingface/llm-swarm include: jpmens/jo — Jo is a command-line utility designed to construct and manipulate JSON objects and arrays directly from shell… catchthetornado/pdf-extract-api. 599yongyang/datasetloom. allenai/olmocr — Olmocr is a distributed document processing framework designed to convert PDF and image files into structured… bytedance/dolphin — Dolphin is a multimodal layout analyzer and image-to-structure converter that transforms photographed or digital… argilla-io/distilabel — Distilabel is a framework for synthetic data and AI feedback for engineers who need fast, reliable and scalable…

Open-source alternatives to Llm Swarm

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  • allenai/olmocrallenai avatar

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    Olmocr is a distributed document processing framework designed to convert PDF and image files into structured markdown. It functions as a vision-based document parser that utilizes multimodal neural networks to interpret complex visual layouts and translate them into standardized text representations. The system operates as a remote inference orchestrator, offloading heavy document analysis tasks to external servers or cloud APIs to minimize local computational requirements. By employing a stateless worker architecture, it decouples document ingestion from inference, allowing for the distribu

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See all 30 alternatives to Llm Swarm→