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AI モデル 85004
- swin_tiny_patch4_window7_224.ms_in1k↗
timm
A Swin Transformer image classification model. Pretrained on ImageNet-1k by paper authors. - **Model Type:** Image classification / feature backbone - **Model Stats:** - Params (M): 28.3 - GMACs: 4.5 - Activations (M): 17.1 - Image size: 224 x 224 - **Papers:** - Swin Transformer: Hierarchical Vision Transformer using Shifted Windows: https://arxiv.org/abs/2103.14030 - **Original:** https://github.com/microsoft/Swin-Transformer - **Dataset:** ImageNet-1k Explore the dataset and runtime metrics of this model in timm model results.
- distilbert-base-uncased-mnli↗
typeform
- Model Details - How to Get Started With the Model - Uses - Risks, Limitations and Biases - Training - Evaluation - Environmental Impact **Model Description:** This is the uncased DistilBERT model fine-tuned on Multi-Genre Natural Language Inference (MNLI) dataset for the zero-shot classification task. - **Developed by:** The Typeform team. - **Model Type:** Zero-Shot Classification - **Language(s):** English - **License:** Unknown - **Parent Model:** See the distilbert base uncased model for more information about the Distilled-BERT base model. **CONTENT WARNING: Readers should be aware this section contains content that is disturbing, offensive, and can propagate historical and current stereotypes.**
- UI-TARS-2B-SFT↗
字节跳动
- Qwen2.5-Coder-7B-Instruct-bnb-4bit↗
unsloth
We have a Qwen 2.5 (all model sizes) free Google Colab Tesla T4 notebook. Also a Qwen 2.5 conversational style notebook. 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. - This conversational notebook is useful for ShareGPT ChatML / Vicuna templates. - This text completion notebook is for raw text. This DPO notebook replicates Zephyr. - \* Kaggle has 2x T4s, but we use 1. Due to overhead, 1x T4 is 5x faster.
- Xing4.0-29B-A4B-Q4_K_M↗
WearItAIteam
- 12bgguf↗
Abc7347
- colSmol-256M-merged↗
akshayballal
- GLM-5.3-INT4-FP8Mix↗
AlayaNeW
- OLMo-2-1124-13B↗
allenai
We introduce OLMo 2, a new family of 7B and 13B models trained on up to 5T tokens. These models are on par with or better than equivalently-sized fully-open models, and competitive with open-weight models from Meta and Mistral on English academic benchmarks. OLMo is a series of **O**pen **L**anguage **Mo**dels designed to enable the science of language models. These models are trained on the Dolma dataset. We are releasing all code, checkpoints, logs (coming soon), and associated training details. The core models released in this batch include the following: OLMo 2 will be supported in the next version of Transformers, and you need to install it from the main branch using:
- Gemma-4-26B-A4B-NVFP4↗
AxionML