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Your data model is your destiny

Gemini 3.0 spotted in the wild through A/B testing

New Coding Models and Integrations

TaxCalcBench: Evaluating Frontier Models on the Tax Calculation Task

Intel Announces Inference-Optimized Xe3P Graphics Card with 160GB VRAM

MAML – a new configuration language (similar to JSON, YAML, and TOML)

4x faster LLM inference (Flash Attention guy's company)

Ohno Type School

Representation Engineering

[R][P] We compress any BF16 model to ~70% size during inference, while keeping the output LOSSLESS so that you can fit in more context or run larger models.

We compress any BF16 model to ~70% size during inference, while keeping the output LOSSLESS so that you can fit in more ERP context or run larger models.

How can I be 100% sure that my AI Agent will not fail in production? Any process or industry practice

I benchmarked the Gemma 3 27b QAT models

[D] Would multiple NVIDIA Tesla P100's be cost effective for model training?

Have you tried a Ling-Lite-0415 MoE (16.8b total, 2.75b active) model?, it is fast even without GPU, about 15-20 tps with 32k context (128k max) on Ryzen 5 5500, fits in 16gb RAM at Q5. Smartness is about 7b-9b class models, not bad at deviant creative tasks.

Self-host Local AI platform with Ollama and Open WebUI

What's the best models available today to run on systems with 8 GB / 16 GB / 24 GB / 48 GB / 72 GB / 96 GB of VRAM today?

[D] Avoiding cold starts with model snapshots — 2 GPUs, 50 LLMs, no containers

deepspeedai

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DeepSpeed

DeepSpeed is a deep learning optimization library that makes distributed training and inference easy, efficient, and effective.

microsoft

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onnxruntime

ONNX Runtime: cross-platform, high performance ML inferencing and training accelerator

huggingface

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pytorch-image-models

The largest collection of PyTorch image encoders / backbones. Including train, eval, inference, export scripts, and pretrained weights -- ResNet, ResNeXT, EfficientNet, NFNet, Vision Transformer (ViT), MobileNetV4, MobileNet-V3 & V2, RegNet, DPN, CSPNet, Swin Transformer, MaxViT, CoAtNet, ConvNeXt, and more

aws

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amazon-sagemaker-examples

Example 📓 Jupyter notebooks that demonstrate how to build, train, and deploy machine learning models using 🧠 Amazon SageMaker.

Deci-AI

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super-gradients

Easily train or fine-tune SOTA computer vision models with one open source training library. The home of Yolo-NAS.

modelscope

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modelscope

ModelScope: bring the notion of Model-as-a-Service to life.