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AI 모델 84759

• ultratensor-models↗

  NagusameCS

• capybara-math-smol-4.1B-2509-preview-GGUF↗

  NaruseShiroha

• HyperCLOVAX-SEED-Think-32B-GGUF↗

  naver-ellm

• Qwen3.6-27B-DSV4Pro-Thinking-Distill↗

  nerkyor

• LazyMix-Uncensored↗

  nesaorg

• ProtGPT2↗

  nferruz

  We have released ProtGPT3! The models show much higher performance across tasks, so we strongly recommend updating your current protocols and starting to use our newer versions. See the related paper here, and download the models here. Let us know if you have any questions! ProtGPT2 (peer-reviewed paper) is a language model that speaks the protein language and can be used for de novo protein design and engineering. ProtGPT2 generated sequences conserve natural proteins' critical features (amino acid propensities, secondary structural content, and globularity) while exploring unseen regions of the protein space. ProtGPT2 is based on the GPT2 Transformer architecture and contains 36 layers with a model dimensionality of 1280, totalling 738 million parameters.

• gpt4all-j-unchained-epoch_1↗

  nomic-ai

• blessed-sdxl-vae-fp16-fix↗

  nubby

• bigvgan_v2_24khz_100band_256x↗

  NVIDIA

  - **Jul 2024 (v2.3):** - General refactor and code improvements for improved readability. - Fully fused CUDA kernel of anti-alised activation (upsampling + activation + downsampling) with inference speed benchmark. - **Jul 2024 (v2.2):** The repository now includes an interactive local demo using gradio. - **Jul 2024 (v2.1):** BigVGAN is now integrated with 🤗 Hugging Face Hub with easy access to inference using pretrained checkpoints. We also provide an interactive demo on Hugging Face Spaces.

• NVIDIA-NemotronLabs-RE-USE-laughter↗

  NVIDIA

  NVIDIA NemotronLabs RE-USE-laughter is a 9.6-million-parameter **multilingual universal speech enhancement (USE)** model designed to restore speech quality across a wide range of real-world degradations while preserving speech fidelity. It has the following desirable properties: - **This model better preserves laughter while restoring the quality of the input speech.** - Robustness to **diverse degradations**, including additive noise, reverberation, clipping, bandwidth limitation, codec artifacts, packet loss and low-quality mics. - Support for **multiple input sampling rates**, including 8, 16, 22.05, 24, 32, 44.1, and 48 kHz. - Strong **language-agnostic** capability, enabling effective performance across different languages. (Note: For overlapping speech, this model is trained to preserve the main speaker while suppressing other speakers.) Comparison with other open-source USE models on the (subsets) of the URGENT 2025 non-blind test set, referenced against original anechoic clean speech.