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AI 모델 84997

• cleandift↗

  CompVis

• PP-OCRv6-medium-det-GGUF↗

  cstr

• sam2.1_hiera_tiny↗

  danelcsb

• Toto-2.0-1B↗

  Datadog

  Toto (Time Series Optimized Transformer for Observability) is a family of time series foundation models for multivariate forecasting developed by Datadog. Toto 2.0 is the current generation, featuring u-μP-scaled transformers ranging from 4m to 2.5B parameters, all trained from a single recipe. Forecast quality improves reliably with parameter count across the family. The family sets a new state of the art on three forecasting benchmarks: BOOM, our observability benchmark; GIFT-Eval, the standard general-purpose benchmark; and the recent contamination-resistant TIME benchmark. Every Toto 2.0 size sits on or near the Pareto frontier on both BOOM and GIFT-Eval. The three largest sizes rank first, second, and third among foundation models on GIFT-Eval CRPS rank. On TIME, Toto 2.0 sizes take the top three spots on every metric, ahead of every other external foundation model evaluated.

• who↗

  desert-ant-labs

• deepcogito.cogito-v1-preview-llama-3B-GGUF↗

  DevQuasar-13

• Qwen.Qwen2.5-VL-7B-Instruct-GGUF↗

  DevQuasar-6

• Alibaba-Apsara.DASD-4B-Thinking-GGUF↗

  DevQuasar

• xai-org.grok-2-GGUF↗

  DevQuasar

• fasttext-fa-vectors↗

  facebook