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AI Models 84759

  • YOLO26-seg-ExecuTorch↗

    software-mansion

  • OpenHermes-2.5-Mistral-7B↗

    teknium

    *In the tapestry of Greek mythology, Hermes reigns as the eloquent Messenger of the Gods, a deity who deftly bridges the realms through the art of communication. It is in homage to this divine mediator that I name this advanced LLM "Hermes," a system crafted to navigate the complex intricacies of human discourse with celestial finesse.* OpenHermes 2.5 Mistral 7B is a state of the art Mistral Fine-tune, a continuation of OpenHermes 2 model, which trained on additional code datasets. Potentially the most interesting finding from training on a good ratio (est. of around 7-14% of the total dataset) of code instruction was that it has boosted several non-code benchmarks, including TruthfulQA, AGIEval, and GPT4All suite. It did however reduce BigBench benchmark score, but the net gain overall is significant.

  • Qwen3.8-Flash-Next-MLX-4bit-MTP↗

    TensorFold

    A uniform 4-bit MLX conversion of Qwen/Qwen3.8-Flash-Next , rebuilt directly from the official BF16 checkpoint with the model's native MTP draft block preserved. This repository contains the standard uniform 4-bit release. Eligible language-model and native-MTP modules use MLX affine quantisation at group size 32. Multimodal modules and MoE router gates remain in BF16. Group size 32 also covers the model's 160-wide hashed n-gram embedding tables. The upstream tokenizer, chat template, vision processor, generation configuration, licence, and native MTP configuration are retained.

  • Marcoroni-neural-chat-7B-v1-GGUF↗

    TheBloke

  • Meta-Llama-3.1-8B-Instruct-GGUF↗

    ThomasBaruzier

  • wavlm-large-msp-podcast-emotion-dim↗

    tiantiaf

  • SmallThinker-21BA3B-Instruct-GGUF↗

    Tiiny

  • tf_efficientnet_lite2.in1k↗

    timm

  • tf_efficientnetv2_s.in21k_ft_in1k↗

    timm

    A EfficientNet-v2 image classification model. Trained on ImageNet-21k and fine-tuned on ImageNet-1k in Tensorflow by paper authors, ported to PyTorch by Ross Wightman. - **Model Type:** Image classification / feature backbone - **Model Stats:** - Params (M): 21.5 - GMACs: 5.4 - Activations (M): 22.7 - Image size: train = 300 x 300, test = 384 x 384 - **Papers:** - EfficientNetV2: Smaller Models and Faster Training: https://arxiv.org/abs/2104.00298 - **Dataset:** ImageNet-1k - **Pretrain Dataset:** ImageNet-21k - **Original:** https://github.com/tensorflow/tpu/tree/master/models/official/efficientnet Explore the dataset and runtime metrics of this model in timm model results.

  • Z-Image-Turbo-pencil-sketch↗

    Ttio2