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AI Models 84760

• BindWeave-GGUF↗

  vantagewithai

• NVIDIA-Nemotron-Nano-12B-v2-VL-BF16-GGUF↗

  Vastined

• gemma-4-E4B-it-W4A16-AutoRound-GPTQ↗

  Vishva007

  This repository hosts **W4A16 INT4-quantized** versions of `google/gemma-4-E4B-it`, a multimodal mixture-of-experts model supporting text, vision, and audio inputs. Two quantized variants are available: > **Note on MTP / Speculative Decoding:** > If you want to use the official speculative decoding assistant model (`google/gemma-4-E4B-it-assistant`) for MTP support, it is recommended to use the `vllm/vllm-openai:gemma4-0505-cu129` Docker image, which includes newer Gemma 4 support and decoding patches. > > Due to INT4 quantization, the assistant acceptance rate may be lower compared to the original unquantized `google/gemma-4-E4B-it` model. > **Note:** Only the language model (LM) layers are quantized to INT4. The vision tower, audio tower, and multimodal projectors are kept at full precision (BF16) to preserve multimodal quality.

• Qwen3.6-35B-A3B-DSPARK-GGUF↗

  williamliao

• Zamba2-2.7B↗

  Zyphra

  Zamba2-2.7B is a hybrid model composed of state-space and transformer blocks. It broadly follows the Zamba architecture which consists of a Mamba backbone alternating with shared transformer blocks (see diagram in Model Details). Zamba2-2.7B possesses three major improvements over Zamba1: 2.) Instead of a single shared attention block, we utilize two shared attention blocks which are interleaved in an ABAB pattern throughout the network. 3.) We apply a LoRA projector to each shared MLP block, which allows the network to specialize the MLPs at each invocation of the shared layer across depth. LoRA enables us to add depth-specialization for only a minimal increase in total parameter count.

• Ornith1.5-9B-3MPER0RR-abliterated↗

  3MPER0RR

• Std-SFT-Passage-9B↗

  AdarshSingh7647

• Ahadadada_Jailbreak_Qwen3.8_27B↗

  ahadadada

• BFS-Best-Face-Swap↗

  Alissonerdx

  BFS is a collection of LoRAs for face, head, and body replacement across Qwen Image 2.1, Qwen Image Edit 2509/2511, Flux 2 Klein, Krea 2, and experimental LTX-2 workflows. Each release has its own base-model, input-order, prompt, and workflow contract. Use the guide for the exact version you are loading. - BFS Head V1 / V1.1 for Qwen Image 2.1 - BFS Body Swap V1.0 for Qwen Image 2.1 - Qwen Image Edit 2509/2511 - Flux 2 Klein - Krea 2 - Experimental LTX-2 weights - Use the LoRA with its matching base model whenever possible. - Follow the input order in the version guide; several BFS head releases intentionally use body first and reference face second. - Start at LoRA strength `1.0`, then adjust for the base model, resolution, and reference image. - The examples and workflows in this repository are demonstrations, not a guarantee of identical results on every image. - Do not use or share results involving public figures or people who have not given consent.

• Fun-ASR-Nano-2512-vllm↗

  allendou