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AI 模型 84759

• Blake-XTM-Arc-3B-V1-GGUF↗

  Flexan

• hin-deva-10mb-ppt-Dp-100mb-packed-bfdiso_seed455↗

  francesca9805

• Laya-GGUF↗

  ggml-org

  This is a decision model, to be used via `/v1/systemone` API. See https://github.com/ggml-org/llama.cpp/pull/29818 > [!IMPORTANT] > This model is automatically converted using https://github.com/ggml-org/convert

• Qwen3-ASR-0.6B-GGUF↗

  ggml-org

  This model is converted from Qwen/Qwen3-ASR-0.6B to GGUF using `convert_hf_to_gguf.py`

• Gemini 3.8 Flash (Medium)↗

  Google

• gemma-4-31B-it-qat-q4_0-gguf↗

  Google

  Hugging Face | GitHub | Launch Blog | Documentation | Technical Report > [!Note] > This model card is for the new versions of the Gemma 4 family optimized with Quantization-Aware Training (QAT), which allows preserving similar quality to bfloat16 while dramatically reducing the memory requirements to load the model. > Four versions of the QAT checkpoints are available: > * **Unquantized QAT checkpoints** (Q4_0): Half-precision weights extracted from the QAT pipeline, ideal for custom downstream compilation and research. Available for Gemma 4 E2B, E4B, 12B, 26B A4B, and 31B, and their drafter models. > * **GGUF** (Q4_0): Ready-to-deploy formats for broad ecosystem compatibility. Available for Gemma 4 E2B, E4B, 12B, 26B A4B, and 31B. > * **Mobile-optimized** (wNa8o8): A custom schema engineered explicitly for mobile hardware efficiency. It features targeted 2-bit decoding layers, optimized KV caches, and static activations to maximize VRAM savings. Available for Gemma 4 E2B and E4B. > * **Compressed Tensors** (w4a16): QAT checkpoints serialized in the compressed-tensors format for native, optimized inference with vLLM. Available for Gemma 4 E2B, E4B, 12B, and 31B. > * **Assistant Compatibility**: When using multi-token prediction (speculative decoding) with an assistant model alongside a QAT target model, the assistant model must also be a QAT checkpoint with the same precision to ensure compatibility. Gemma is a family of open models built by Google DeepMind. Gemma 4 models are multimodal, handling text and image input (with audio supported on E2B, E4B, and 12B) and generating text output. This release includes open-weights models in both pre-trained and instruction-tuned variants. Gemma 4 features a context window of up to 256K tokens and maintains multilingual support in over 140 languages.

• multiberts-seed_4-step_1800k↗

  Google

• parakeet-tdt-0.6b-v3-gguf↗

  handy-computer

  GGUF conversions of nvidia/parakeet-tdt-0.6b-v3 for use with transcribe.cpp. Ported from upstream commit 6d590f7, pinned 2026-04-16. Validated against the NeMo reference at transcribe.cpp commit bf0d0b7 on 2026-04-18. Offline multilingual speech-to-text covering 25 European languages. A Conformer encoder with a TDT/RNNT transducer decoder. Takes a 16 kHz mono WAV and produces a transcript with optional token-level timestamps. Not a streaming model and does not translate.

• GemmaDGAF-2B↗

  hecan3d

• opus-mt-tc-big-fr-en↗

  Helsinki-NLP