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AI モデル 85003

• use-cmlm-multilingual↗

  sentence-transformers

• Arctic-Text2SQL-R1-7B↗

  Snowflake

• baku-13b↗

  sudy-super

• gLM2_150M↗

  tattabio

• eva_large_patch14_196.in22k_ft_in22k_in1k↗

  timm

  An EVA image classification model. Pretrained on ImageNet-22k with masked image modeling (using EVA-CLIP as a MIM teacher) and fine-tuned on ImageNet-22k then on ImageNet-1k by paper authors. NOTE: `timm` checkpoints are float32 for consistency with other models. Original checkpoints are float16 or bfloat16 in some cases, see originals if that's preferred. - **Model Type:** Image classification / feature backbone - **Model Stats:** - Params (M): 304.1 - GMACs: 61.6 - Activations (M): 63.5 - Image size: 196 x 196 - **Papers:** - EVA: Exploring the Limits of Masked Visual Representation Learning at Scale: https://arxiv.org/abs/2211.07636 - **Pretrain Dataset:** - ImageNet-22k - ImageNet-22k - **Dataset:** ImageNet-1k - **Original:** - https://github.com/baaivision/EVA - https://huggingface.co/BAAI/EVA

• gemma-3↗

  tiny-random

  This tiny model is for debugging. It is randomly initialized with the config adapted from google/gemma-3-27b-it.

• wav2vec2-large-xlsr-53-mongolian↗

  tugstugi

• gemma-4-E2B-it-unsloth-bnb-4bit↗

  unsloth

  Gemma 4 can now be run and fine-tuned in Unsloth Studio. Read our guide. See all versions of Gemma 4 (GGUF, 16-bit etc.) in our collection. 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 small models) 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.

• ThinkingCap-Qwen3.8-27B-MIX_GGUF↗

  vmarcelo

• LaBSE↗

  Xenova