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AI モデル 85004

• vit_base_patch16_384.augreg_in21k_ft_in1k↗

  timm

  A Vision Transformer (ViT) image classification model. Trained on ImageNet-21k and fine-tuned on ImageNet-1k (with additional augmentation and regularization) in JAX by paper authors, ported to PyTorch by Ross Wightman. - **Model Type:** Image classification / feature backbone - **Model Stats:** - Params (M): 86.9 - GMACs: 49.4 - Activations (M): 48.3 - Image size: 384 x 384 - **Papers:** - How to train your ViT? Data, Augmentation, and Regularization in Vision Transformers: https://arxiv.org/abs/2106.10270 - An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale: https://arxiv.org/abs/2010.11929v2 - **Dataset:** ImageNet-1k - **Pretrain Dataset:** ImageNet-21k - **Original:** https://github.com/google-research/vision_transformer Explore the dataset and runtime metrics of this model in timm model results.

• mistral-7b-instruct-v0.3↗

  unsloth

  We have a Google Colab Tesla T4 notebook for Mistral v3 7b here: https://colab.research.google.com/drive/1_yNCks4BTD5zOnjozppphh5GzMFaMKq_?usp=sharing For conversational ShareGPT style and using Mistral v3 Instruct: https://colab.research.google.com/drive/15F1xyn8497_dUbxZP4zWmPZ3PJx1Oymv?usp=sharing All notebooks are **beginner friendly**! Add your dataset, click "Run All", and you'll get a 2x faster finetuned model which can be exported to GGUF, vLLM or uploaded to Hugging Face.

• nli-deberta-v3-small↗

  Xenova

• Qwen2.5-0.5B-Instruct-Gensyn-Swarm-sprightly_gregarious_barracuda↗

  Zeniang

• Qwen3.8-27B-Cold-Fusion-GAIN-V1.1-YMQ-GGUF↗

  zerodigest

• Unsloth-Qwen3.8-27B-UD-KQVQ4-IQ3Floor-10G-MTP-GGUF↗

  zhangrover

• MolGen-large↗

  zjunlp

• Yi-6B-Chat↗

  01-ai

  - they might want nothing more than destruction itself rather then anything else from their quest after immortality (and maybe someone should tell them about modern medicine)? In any event though – one thing remains true regardless : whether or not success comes easy depends entirely upon how much effort we put into conquering whatever challenges lie ahead along with having faith deep down inside ourselves too ;) So let’s get started now shall We?" pipeline_tag: text-generation --- - What is Yi? - Introduction - Models - Chat models - Base models - Model info - News - How to use Yi? - Quick start - Choose your path - pip - docker - llama.cpp - conda-lock - Web demo - Fine-tuning - Quantization - Deployment - FAQ - Learning hub - Why Yi? - Ecosystem - Upstream - Downstream - Serving - Quantization - Fine-tuning - API - Benchmarks - Base model performance - Chat model performance - Tech report - Citation - Who can use Yi? - Misc. - Acknowledgements - Disclaimer - License - 🤖 The Yi series models are the next generation of open-source large language models trained from scratch by 01.AI.

• BArtstyle-Blue-Archive-Artstyle-LoRA-for-Krea2↗

  4BEraser

• indicwav2vec-hindi↗

  ai4bharat