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pice35408784b54431987c4d13c457b9cd / detr-resnet-50-sku110k_a14147223246991360310908
0 0
检测 Transformer（DETR）模型在 SKU110K 目标检测（含 8000 张带标注图像）数据集上进行了端到端训练。与原始模型相比，主要区别在于它有 400 个查询数量（num_queries），并且是在 SKU110K 数据集上进行了预训练。
Updated 2025-01-02 14:20:04 +08:00
gi111f11cb7f354a74a8c123f5b155498e / Mistral-Nemo-Instruct-2407_a14147247173136384657479
0 0
Mistral-Nemo-Instruct-2407
Updated 2025-01-02 13:55:31 +08:00
pice35408784b54431987c4d13c457b9cd / yolos-small-finetuned-license-plate-detection_a14147096336265216444923
0 0
该模型是在来自 Roboflow 的车牌识别数据集上对 hustvl/yolos-small 进行微调后的版本，其训练集中包含 5200 张图像，验证集中包含 380 张图像。原始的 YOLOS 模型是在 COCO 2017 目标检测数据集（含 11.8 万张带标注图像）上进行微调的。
Updated 2025-01-02 13:44:14 +08:00
pice35408784b54431987c4d13c457b9cd / yolos-fashionpedia_a14146128397332480885694
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这是一个针对时尚领域经过微调的目标检测模型。
Updated 2025-01-02 11:41:03 +08:00
gi111f11cb7f354a74a8c123f5b155498e / Qwen2-Audio-7B-Instruct_a14145662504529920880333
0 0
Qwen2-Audio-7B-Instruct
Updated 2025-01-02 11:35:02 +08:00
gi111f11cb7f354a74a8c123f5b155498e / fish-speech-1.5_a14145515045515264908091
0 0
fish-speech-1.5
Updated 2025-01-02 10:29:31 +08:00
gi111f11cb7f354a74a8c123f5b155498e / OuteTTS-0.2-500M_a14145197344813056170454
0 0
OuteTTS-0.2-500M
Updated 2025-01-02 10:20:00 +08:00
gi111f11cb7f354a74a8c123f5b155498e / CosyVoice-300M_a14145156848283648201208
0 0
CosyVoice-300M
Updated 2025-01-02 10:10:50 +08:00
gi111f11cb7f354a74a8c123f5b155498e / CosyVoice-300M-Instruct_a14145133587722240943972
0 0
CosyVoice-300M-Instruct
Updated 2025-01-02 09:40:48 +08:00
gi111f11cb7f354a74a8c123f5b155498e / EXAONE-3.5-7.8B-Instruct_a14125166997008384632002
Python 0 0
EXAONE-3.5-7.8B-Instruct
Updated 2024-12-31 20:09:06 +08:00
gi111f11cb7f354a74a8c123f5b155498e / granite-3.1-2b-instruct_a14125402442035200619941
Text 0 0
granite-3.1-2b-instruct
Updated 2024-12-31 17:26:16 +08:00
gi111f11cb7f354a74a8c123f5b155498e / EXAONE-3.5-2.4B-Instruct_a14125146540077056541976
Python 0 0
EXAONE-3.5-2.4B-Instruct
Updated 2024-12-31 16:45:02 +08:00
pice35408784b54431987c4d13c457b9cd / swin-large-patch4-window7-224_a14125352540696576932871
0 0
在 ImageNet-1k 上以 224x224 的分辨率训练的 Swin Transformer 模型。
Updated 2024-12-31 16:20:10 +08:00
pice35408784b54431987c4d13c457b9cd / AI-image-detector_a14125217224323072262254
0 0
利用视觉 Transformer（ViT）模型来预测一幅艺术图像是否是通过人工智能生成的。
Updated 2024-12-31 15:21:36 +08:00
pice35408784b54431987c4d13c457b9cd / efficientnet-b1_a14125090550312960994889
0 0
在 ImageNet-1k 上以 240x240 的分辨率训练的 EfficientNet 模型。
Updated 2024-12-31 15:06:05 +08:00
gi111f11cb7f354a74a8c123f5b155498e / KaLM-embedding-multilingual-mini-instruct-v1_a14123280559894528370540
Python 0 0
KaLM-embedding-multilingual-mini-instruct-v1
Updated 2024-12-31 12:43:03 +08:00
gi111f11cb7f354a74a8c123f5b155498e / InternVL2_5-8B_a14123014239023104738976
Python 0 0
InternVL2_5-8B
Updated 2024-12-31 12:21:45 +08:00
gi111f11cb7f354a74a8c123f5b155498e / Index-1.9B-Chat_a14114230254694400156844
Python 0 0
Index-1.9B-Chat
Updated 2024-12-31 10:57:15 +08:00
gi111f11cb7f354a74a8c123f5b155498e / stella_en_400M_v5_a14122951856353280399733
Python 0 0
stella_en_400M_v5
Updated 2024-12-31 10:56:38 +08:00
gi111f11cb7f354a74a8c123f5b155498e / gme-Qwen2-VL-2B-Instruct_a14122304306802688376722
0 0
gme-Qwen2-VL-2B-Instruct
Updated 2024-12-31 10:39:23 +08:00