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AI Models 84759

• vi-humanizer-gemma-4-e2b-i1-GGUF↗

  mradermacher

• XORTRON.CriminalComputing.2026.27B.Instruct-GGUF↗

  mradermacher

• Qwythos-9B-Claude-Mythos-5-1M-GGUF↗

  N8STORM

• nb-whisper-medium↗

  NbAiLab

• N-ATLaS↗

  NCAIR1

• bert-tiny-sts-last-pooling↗

  NeuML

• v6-mixed-25k-lower-shared-deu-ell-sequential_interleaved↗

  nikitastheo

• gpt2-greek↗

  nikokons

• Cosmos-Embed1-224p↗

  NVIDIA

  **Cosmos-Embed1** is a joint video-text embedder tailored for physical AI. It can be used for text-to-video retrieval, inverse video search, semantic deduplication, zero-shot and k-nearest-neighbors (kNN) classification, and as a base model for video curation tasks. It has state-of-the-art (SOTA) performance on autonomous vehicle (AV) and robotics datasets, while maintaining competitive performance in general domains. This model is ready for commercial use. The Cosmos-Embed1 release includes the following embedders: * **Cosmos-Embed1** * Cosmos-Embed1-224p (optimized with 8 frames and 224x224 input resolution, 256-dim output text and video embeddings) * Cosmos-Embed1-336p (optimized with 8 frames and 336x336 input resolution, 768-dim output text and video embeddings) * Cosmos-Embed1-448p (optimized with 8 frames and 448x448 input resolution, 768-dim output text and video embeddings) Note, while each checkpoint was optimized at a specific fixed resolution (and default to these), they all support arbitrary non-square resolutions.

• PMRF_blind_face_image_restoration↗

  ohayonguy