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AI Models 84759

  • Lite-Beam-27B↗

    tablinum

  • clip-vit-large-patch14_mnist↗

    tanganke

    Adam Optimizer with a constant learning rate 1e-5 for 4000 steps training (batch_size=32). Only the vision encoder is fine-tuned.

  • bbb3↗

    tao1000

  • Granite-4.0-H-350M-BE-GGUF↗

    taronaeo

    **Model Summary:** Granite-4.0-H-350M is a lightweight instruct model finetuned from *Granite-4.0-H-350M-Base* using a combination of open source instruction datasets with permissive license and internally collected synthetic datasets. This model is developed using a diverse set of techniques including supervised finetuning, reinforcement learning, and model merging. - **Developers:** Granite Team, IBM - **HF Collection:** Granite 4.0 Nano Language Models HF Collection - **GitHub Repository:** ibm-granite/granite-4.0-nano-language-models - **Website**: Granite Docs - **Release Date**: October 28, 2025 - **License:** Apache 2.0 **Supported Languages:** English, German, Spanish, French, Japanese, Portuguese, Arabic, Czech, Italian, Korean, Dutch, and Chinese. Users may fine-tune Granite 4.0 Nano models to support languages beyond those included in this list.

  • 13B-HyperMantis-GGUF↗

    TheBloke

  • COTHuginn-4.5-19B-GGUF↗

    TheBloke

  • Mixtral-8x7B-Instruct-v0.1-LimaRP-ZLoss-DARE-TIES-GGUF↗

    TheBloke

  • StableBeluga2-70B-GPTQ↗

    TheBloke

  • beitv2_base_patch16_224.in1k_ft_in22k↗

    timm

    A BEiT-v2 image classification model. Trained on ImageNet-1k with self-supervised masked image modelling (MIM) using a VQ-KD encoder as a visual tokenizer (via OpenAI CLIP B/16 teacher). Fine-tuned on ImageNet-22k. - **Model Type:** Image classification / feature backbone - **Model Stats:** - Params (M): 102.6 - GMACs: 17.6 - Activations (M): 23.9 - Image size: 224 x 224 - **Papers:** - BEiT v2: Masked Image Modeling with Vector-Quantized Visual Tokenizers: https://arxiv.org/abs/2208.06366 - An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale: https://arxiv.org/abs/2010.11929v2 - **Dataset:** ImageNet-22k - **Original:** https://github.com/microsoft/unilm/tree/master/beit2 Explore the dataset and runtime metrics of this model in timm model results.

  • crossvit_9_dagger_240.in1k↗

    timm