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TText generation▧Image generation▷Video generation⌘Code generation◖Speech synthesis♫Music generation⬡3D modeling▤Document analysis
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基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。

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Try it on Argmax Playground (TestFlight) Read the Interspeech 2025 paper for architecture and benchmarks. License: SpeakerKit the Swift framework has MIT license. The models SpeakerKit is built on have CC BY 4 license.

Speech recognition
Input Audio→ Output Text
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ttskit-coreml

argmaxinc

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WhisperKit is part of Argmax OSS, an On-device Speech AI SDK for Apple Silicon: https://github.com/argmaxinc/argmax-oss-swift For real-time transcription with speakers and custom vocabulary, check out Argmax Pro SDK: https://www.argmaxinc.com/blog/argmax-sdk-2

Text generationOpen weights
Input Audio→ Output Text
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LUMINA

argonne

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**Stage-2b endpoint, bias-0 arm** -- long-context forward-KL logit distillation against Qwen3-4B at sequence length 32,768, 294M tokens (141 steps of 2,097,152; micro-batch 1 x 4 ranks x 16 accumulation), from the stage-2a endpoint of this arm. LR halved from stage 2a: mixers 1e-4, inherited weights 1e-5, cosine to 0.1x with 3% warmup; all weights train. 4x B200. Final val KL at 32k **0.2021**, top1-agreement **0.8056**, wikitext-2 PPL (4096 context) **11.93**, from a starting point of 1.1727 / 0.7167 / 12.49. At this same stage the Qwen GDN arm reaches KL 0.2177 / top1 0.7985 and the Qwen Mamba2 arm 0.2336 / 0.7875; see the table below for the bias-1 arm. This is the input to stage-3 on-policy distillation, which has not been run. No downstream evaluation yet. This is a **custom container** (`model_type: qwen3_mamba3`), not a stock architecture, so `trust_remote_code=True` is required. The modeling code is bundled in this repo (`modeling_qwen3_mamba3.py`) and needs no other checkout:

Text generation
Input Text→ Output Text
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> Centralized storage repository for high-performance `.safetensors` model weights, diffusion checkpoints, and assets used across active Hugging Face Spaces. This repository serves as the primary weight host and backend storage vault for generative AI workflows. Storing weights in a single dedicated repository ensures fast loading times, seamless updates, and persistent access for dependent web applications and pipeline runners.

Image generation
Input Text→ Output Image
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