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AI Models 84753

• Qwen3.8-Flash-Next-4bit↗

  rapid-mlx

• GPT2-ChineseDevBench↗

  Recor2d

• ParasiticRogue_-_Merged-RP-Stew-V2-34B-gguf↗

  RichardErkhov

• sarvam-105b↗

  sarvamai

  1. Introduction 2. Architecture 3. Benchmarks - Knowledge & Coding - Reasoning & Math - Agentic 4. Inference - Hugging Face - vLLM - SGLang 5. Footnote 6. Citation **Sarvam-105B** is an advanced Mixture-of-Experts (MoE) model with 10.3B active parameters, designed for superior performance across a wide range of complex tasks. It is highly optimized for complex reasoning, with particular strength in agentic tasks, mathematics, and coding. Sarvam-105B is a top-tier performer, consistently matching or surpassing several major closed-source models and staying within a narrow margin of frontier models across diverse reasoning and agentic benchmarks. It demonstrates exceptional agentic and reasoning capabilities in real-world applications such as web search and technical troubleshooting.

• Noql↗

  shekar-ai

• Llama-3.3-70B-Instruct-GPTQ↗

  shuyuej

• spkrec-ecapa-voxceleb↗

  speechbrain

  This repository provides all the necessary tools to perform speaker verification with a pretrained ECAPA-TDNN model using SpeechBrain. The system can be used to extract speaker embeddings as well. It is trained on Voxceleb 1+ Voxceleb2 training data. For a better experience, we encourage you to learn more about SpeechBrain. The model performance on Voxceleb1-test set(Cleaned) is: This system is composed of an ECAPA-TDNN model. It is a combination of convolutional and residual blocks. The embeddings are extracted using attentive statistical pooling. The system is trained with Additive Margin Softmax Loss. Speaker Verification is performed using cosine distance between speaker embeddings.

• Sugoi-32B-Ultra-GGUF↗

  sugoitoolkit

• Qwen3.5-4B-NVFP4↗

  surogate

• Qwen3.8-2B-heretic↗

  Tanjiro20