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emailA Systems View of LLMs on TPUs.
This book aims to demystify the art of scaling LLMs on TPUs. We try to explain how TPUs work, how LLMs actually run at scale, and how to pick parallelism schemes during training and inference that avoid communication bottlenecks.
Open Universal Machine Intellingence.
E2E Foundation Model Research Platform.
Everything you need to build state-of-the-art foundation models, end-to-end.
Oumi is a fully open-source platform that streamlines the entire lifecycle of foundation models - from data preparation and training to evaluation and deployment. Whether you're developing on a laptop, launching large scale experiments on a cluster, or deploying models in production, Oumi provides the tools and workflows you need.
State-of-the-art Machine Learning for PyTorch, TensorFlow, and JAX.
Transformers provides APIs and tools to easily download and train state-of-the-art pretrained models. Using pretrained models can reduce your compute costs, carbon footprint, and save you the time and resources required to train a model from scratch.
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ONNX Runtime: cross-platform, high performance ML inferencing and training accelerator.
ONNX Runtime inference can enable faster customer experiences and lower costs, supporting models from deep learning frameworks such as PyTorch and TensorFlow/Keras as well as classical machine learning libraries such as scikit-learn, LightGBM, XGBoost, etc.
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Easy, fast, and cheap LLM serving for everyone.
vLLM is a fast and easy-to-use library for LLM inference and serving.
Originally developed in the Sky Computing Lab at UC Berkeley, vLLM has evloved into a community-driven project with contributions from both academia and industry.
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Open Repository of Web Crawl Data.
Common Crawl maintains a free, open repository of web crawl data that can be used by anyone.
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15 trillion tokens of the finest data the 
web has to offer.
The 
FineWeb dataset consists of more than 15T tokens of cleaned and deduplicated english web data from CommonCrawl. The data processing pipeline is optimized for LLM performance and ran on the 
datatrove library, our large scale data processing library.
FineWeb was originally meant to be a fully open replication of 
RefinedWeb, with a release of the full dataset under the ODC-By 1.0 license. However, by carefully adding additional filtering steps, we managed to push the performance of FineWeb well above that of the original RefinedWeb, and models trained on our dataset also outperform models trained on other commonly used high quality web datasets (like C4, Dolma-v1.6, The Pile, SlimPajama, RedPajam2) on our aggregate group of benchmark tasks.
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Partner of Accounting Leaders. Generative AI platform for intelligent accounting.
The preferred partner of accounting leaders.
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The Annual Conference on Neural Information Processing Systems.
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Run local LLMs inside your browser.
Run AI with an API.
Run and fine-tune open-source models. Deploy custom models at scale. All with one line of code.
Thousands of models contributed by our community.
All the latest open-source models are on Replicate.
They’re not just demos — they all actually work and have production-ready APIs.
AI shouldn’t be locked up inside academic papers and demos. Make it real by pushing it to Replicate.
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Groq is Fast AI Inference.
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Discover, download, and run local LLMs.
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A fast tool to read text-based files in a repository or directory, chunk them, and serialize them for LLM consumption.
Explore Agent Recipes
Explore common agent recipes with ready to copy code to improve your LLM applications.
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Stable Point Aware 3D (SPAR3D) can make real-time edits and create the complete structure of a 3D object from a single image in a few seconds. SPAR3D combines the strengths of point-cloud diffusion (probabilistic) and mesh regression (deterministic) to have improved details on the unseen back regions in the input image.
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structured-logprobs is an open-source Python library that enhances OpenAI's structured outputs by providing detailed information about token log probabilities.
This library is designed to offer valuable insights into the reliability of an LLM's structured outputs. It works with OpenAI's Structured Outputs, a feature that ensures the model consistently generates responses adhering to a supplied JSON Schema. This eliminates concerns about missing required keys or hallucinating invalid values.
We wrote this glossary to solve a problem we ran into working with GPUs here at Modal : the documentation is fragmented, making it difficult to connect concepts at different levels of the stack, like Streaming Multiprocessor Architecture , Compute Capability , and nvcc compiler flags .
Open weights LLM for French, English, German, Spanish and Italian.
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-france @ Jean-Pierre LORRE's LinkedIn
LLM génératifs ouverts et performants.
Le Consortium OpenLLM France réunit 17 acteurs qui se sont rassemblés dans le prolongement de la création de la communauté OpenLLM France qui fédère à ce jour un écosystème de près de 200 entités (laboratoires publics de recherche, fournisseurs potentiels de données, acteurs technologiques spécialisés, fournisseurs de cas d'usage...). Ces acteurs échangent de manière publique et transparente depuis le début de l’été 2023 sur le serveur Discord de la communauté.