model_id stringlengths 7 105 | model_card stringlengths 1 130k | model_labels listlengths 2 80k |
|---|---|---|
OttoYu/Image-place |
## Validation Metrics
- Loss: 0.416
- Accuracy: 0.880
- Macro F1: 0.851
- Micro F1: 0.880
- Weighted F1: 0.866
- Macro Precision: 0.917
- Micro Precision: 0.880
- Weighted Precision: 0.913
- Macro Recall: 0.857
- Micro Recall: 0.880
- Weighted Recall: 0.880 | [
"badland",
"bamboo forest",
"forest",
"reservoir",
"sandy surface: mudflat",
"urban",
"waterbodies"
] |
tcvrishank/vit-bach-demo |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# vit-bach-demo
This model is a fine-tuned version of [google/vit-base-patch16-224](https://huggingface.co/google/vit-base-patch16... | [
"benign",
"insitu",
"invasive",
"normal"
] |
OttoYu/TreeDisease | ## Validation Metrics
- Loss: 1.558
- Accuracy: 0.564
- Macro F1: 0.488
- Micro F1: 0.564
- Weighted F1: 0.516
- Macro Precision: 0.503
- Micro Precision: 0.564
- Weighted Precision: 0.542
- Macro Recall: 0.545
- Micro Recall: 0.564
- Weighted Recall: 0.564 | [
"agrilus planipennis 扁豆",
"annosum root rot 番荔枝根腐病",
"leaf blister 葉泡",
"leaf spots 葉斑",
"littleleaf disease 小葉病",
"loblolly pine decline 火炬松衰落",
"needle blights 針葉枯病",
"needle rusts 針葉銹病",
"powdery mildew 白粉病",
"root rots 根腐病",
"rots and decays 腐爛",
"stem decays 莖腐爛",
"anthracnose 炭疽病",
"... |
tcvrishank/fun |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# fun
This model is a fine-tuned version of [google/vit-base-patch16-224](https://huggingface.co/google/vit-base-patch16-224) on t... | [
"benign",
"insitu",
"invasive",
"normal"
] |
OttoYu/LeafCondition |
## Validation Metrics
- Loss: 0.021
- Accuracy: 1.000
- Macro F1: 1.000
- Micro F1: 1.000
- Weighted F1: 1.000
- Macro Precision: 1.000
- Micro Precision: 1.000
- Weighted Precision: 1.000
- Macro Recall: 1.000
- Micro Recall: 1.000
- Weighted Recall: 1.000 | [
"bacteria",
"fungi",
"nematodes",
"normal",
"virus"
] |
Rickyfwh/autotrain-js-classfication-test-2-43390110454 |
# Model Trained Using AutoTrain
- Problem type: Multi-class Classification
- Model ID: 43390110454
- CO2 Emissions (in grams): 3.4952
## Validation Metrics
- Loss: 0.750
- Accuracy: 0.751
- Macro F1: 0.678
- Micro F1: 0.751
- Weighted F1: 0.746
- Macro Precision: 0.726
- Micro Precision: 0.751
- Weighted Precision:... | [
"animal",
"building",
"scenery",
"transport",
"cartoon",
"drink",
"food",
"fruits",
"holiday",
"nature",
"others",
"painting"
] |
tcvrishank/histo_train |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# histo_train
This model is a fine-tuned version of [google/vit-base-patch16-224](https://huggingface.co/google/vit-base-patch16-2... | [
"benign",
"insitu",
"invasive",
"normal"
] |
tcvrishank/histo_train_segformer |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# histo_train_segformer
This model is a fine-tuned version of [nvidia/mit-b0](https://huggingface.co/nvidia/mit-b0) on the imagefo... | [
"benign",
"insitu",
"invasive",
"normal"
] |
tcvrishank/histo_train_swin |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# histo_train_swin
This model is a fine-tuned version of [microsoft/swinv2-tiny-patch4-window8-256](https://huggingface.co/microso... | [
"benign",
"insitu",
"invasive",
"normal"
] |
Xrenya/pvt-tiny-224 |
# Pyramid Vision Transformer (tiny-sized model)
Pyramid Vision Transformer (PVT) model pre-trained on ImageNet-1K (1 million images, 1000 classes) at resolution 224x224, and fine-tuned on ImageNet 2012 (1 million images, 1,000 classes) at resolution 224x224. It was introduced in the paper [Pyramid Vision Transforme... | [
"tench, tinca tinca",
"goldfish, carassius auratus",
"great white shark, white shark, man-eater, man-eating shark, carcharodon carcharias",
"tiger shark, galeocerdo cuvieri",
"hammerhead, hammerhead shark",
"electric ray, crampfish, numbfish, torpedo",
"stingray",
"cock",
"hen",
"ostrich, struthio... |
tcvrishank/histo_train_vit |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# histo_train_vit
This model is a fine-tuned version of [google/vit-base-patch16-224](https://huggingface.co/google/vit-base-patch... | [
"benign",
"insitu",
"invasive",
"normal"
] |
nishadsinghi/swin-tiny-patch4-window7-224-airornot |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# swin-tiny-patch4-window7-224-airornot
This model is a fine-tuned version of [microsoft/swin-tiny-patch4-window7-224](https://hug... | [
"tench, tinca tinca",
"goldfish, carassius auratus",
"great white shark, white shark, man-eater, man-eating shark, carcharodon carcharias",
"tiger shark, galeocerdo cuvieri",
"hammerhead, hammerhead shark",
"electric ray, crampfish, numbfish, torpedo",
"stingray",
"cock",
"hen",
"ostrich, struthio... |
mirzaei2114/vit-aiornot |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# vit-aiornot
This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-pat... | [
"real",
"fake"
] |
therealcyberlord/bigcatvit |
Fine-tuning a Vision Transformer on the Big Cats Dataset
In this project, we fine-tuned a vision transformer on the Big Cats dataset to perform image classification. The Big Cats dataset consists of 2339 images of 10 different types of big cats, including lions, tigers, jaguars, and more.
Our goal was to train a mode... | [
"cheetah",
"lions",
"snow leopard",
"caracal",
"tiger",
"clouded leopard",
"puma",
"jaguar",
"ocelot",
"african leopard"
] |
emanehab/aiornot_eman |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# aiornot_eman
This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-pa... | [
"notai",
"ai"
] |
OttoYu/Tree-Condition |
# 🌳 Tree Condition Classification 樹況分類 (bilingual)
### Model Description
This online application covers 22 most typical tree disease over 290+ images. If you find any trees that has hidden injures, you can classifies with our model and report the tree condition via this form (https://rb.gy/c1sfja). 此在線程式涵蓋22種官方部門樹況分類... | [
"burls 節瘤",
"canker 潰瘍",
"fungal fruiting bodies 真菌子實體",
"galls 腫瘤 ",
"girdling root 纏繞根 ",
"heavy lateral limb 重側枝",
"included bark 內夾樹皮",
"parasitic or epiphytic plants 寄生或附生植物",
"pest and disease 病蟲害",
"poor taper 不良漸尖生長",
"root-plate movement 根基移位 ",
"sap flow 滲液",
"co-dominant branches ... |
Xrenya/pvt-small-224 |
# Pyramid Vision Transformer (small-sized model)
Pyramid Vision Transformer (PVT) model pre-trained on ImageNet-1K (1 million images, 1000 classes) at resolution 224x224, and fine-tuned on ImageNet 2012 (1 million images, 1,000 classes) at resolution 224x224. It was introduced in the paper [Pyramid Vision Transform... | [
"tench, tinca tinca",
"goldfish, carassius auratus",
"great white shark, white shark, man-eater, man-eating shark, carcharodon carcharias",
"tiger shark, galeocerdo cuvieri",
"hammerhead, hammerhead shark",
"electric ray, crampfish, numbfish, torpedo",
"stingray",
"cock",
"hen",
"ostrich, struthio... |
Xrenya/pvt-medium-224 |
# Pyramid Vision Transformer (medium-sized model)
Pyramid Vision Transformer (PVT) model pre-trained on ImageNet-1K (1 million images, 1000 classes) at resolution 224x224, and fine-tuned on ImageNet 2012 (1 million images, 1,000 classes) at resolution 224x224. It was introduced in the paper [Pyramid Vision Transfor... | [
"tench, tinca tinca",
"goldfish, carassius auratus",
"great white shark, white shark, man-eater, man-eating shark, carcharodon carcharias",
"tiger shark, galeocerdo cuvieri",
"hammerhead, hammerhead shark",
"electric ray, crampfish, numbfish, torpedo",
"stingray",
"cock",
"hen",
"ostrich, struthio... |
Xrenya/pvt-large-224 |
# Pyramid Vision Transformer (large-sized model)
Pyramid Vision Transformer (PVT) model pre-trained on ImageNet-1K (1 million images, 1000 classes) at resolution 224x224, and fine-tuned on ImageNet 2012 (1 million images, 1,000 classes) at resolution 224x224. It was introduced in the paper [Pyramid Vision Transform... | [
"tench, tinca tinca",
"goldfish, carassius auratus",
"great white shark, white shark, man-eater, man-eating shark, carcharodon carcharias",
"tiger shark, galeocerdo cuvieri",
"hammerhead, hammerhead shark",
"electric ray, crampfish, numbfish, torpedo",
"stingray",
"cock",
"hen",
"ostrich, struthio... |
SebasV/autotrain-tableros_factibilidad-44246111620 |
# Model Trained Using AutoTrain
- Problem type: Multi-class Classification
- Model ID: 44246111620
- CO2 Emissions (in grams): 0.5450
## Validation Metrics
- Loss: 1.067
- Accuracy: 0.600
- Macro F1: 0.542
- Micro F1: 0.600
- Weighted F1: 0.567
- Macro Precision: 0.583
- Micro Precision: 0.600
- Weighted Precision:... | [
"sin adecuaciones",
"tablero",
"tablero 2 medidores",
"tablero varios medidores"
] |
SebasV/autotrain-tableros_factibilidad-44246111621 |
# Model Trained Using AutoTrain
- Problem type: Multi-class Classification
- Model ID: 44246111621
- CO2 Emissions (in grams): 0.6679
## Validation Metrics
- Loss: 1.097
- Accuracy: 0.200
- Macro F1: 0.167
- Micro F1: 0.200
- Weighted F1: 0.133
- Macro Precision: 0.125
- Micro Precision: 0.200
- Weighted Precision:... | [
"sin adecuaciones",
"tablero",
"tablero 2 medidores",
"tablero varios medidores"
] |
SebasV/autotrain-tableros_factibilidad-44246111622 |
# Model Trained Using AutoTrain
- Problem type: Multi-class Classification
- Model ID: 44246111622
- CO2 Emissions (in grams): 0.1825
## Validation Metrics
- Loss: 1.397
- Accuracy: 0.200
- Macro F1: 0.100
- Micro F1: 0.200
- Weighted F1: 0.080
- Macro Precision: 0.062
- Micro Precision: 0.200
- Weighted Precision:... | [
"sin adecuaciones",
"tablero",
"tablero 2 medidores",
"tablero varios medidores"
] |
SebasV/autotrain-tableros_factibilidad-44246111623 |
# Model Trained Using AutoTrain
- Problem type: Multi-class Classification
- Model ID: 44246111623
- CO2 Emissions (in grams): 0.7280
## Validation Metrics
- Loss: 0.962
- Accuracy: 0.400
- Macro F1: 0.375
- Micro F1: 0.400
- Weighted F1: 0.300
- Macro Precision: 0.333
- Micro Precision: 0.400
- Weighted Precision:... | [
"sin adecuaciones",
"tablero",
"tablero 2 medidores",
"tablero varios medidores"
] |
SebasV/autotrain-tableros_factibilidad-44246111624 |
# Model Trained Using AutoTrain
- Problem type: Multi-class Classification
- Model ID: 44246111624
- CO2 Emissions (in grams): 0.3630
## Validation Metrics
- Loss: 1.413
- Accuracy: 0.400
- Macro F1: 0.375
- Micro F1: 0.400
- Weighted F1: 0.400
- Macro Precision: 0.375
- Micro Precision: 0.400
- Weighted Precision:... | [
"sin adecuaciones",
"tablero",
"tablero 2 medidores",
"tablero varios medidores"
] |
platzi/platzi-vit-model-andres-galvis |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# platzi-vit-model-andres-galvis
This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/... | [
"angular_leaf_spot",
"bean_rust",
"healthy"
] |
sauriopqno/autotrain-enfermedadespt2-44370111920 |
# Model Trained Using AutoTrain
- Problem type: Multi-class Classification
- Model ID: 44370111920
- CO2 Emissions (in grams): 0.7149
## Validation Metrics
- Loss: 0.180
- Accuracy: 0.950
- Macro F1: 0.950
- Micro F1: 0.950
- Weighted F1: 0.950
- Macro Precision: 0.950
- Micro Precision: 0.950
- Weighted Precision:... | [
"escarlatina",
"rubeola",
"sano",
"varicela"
] |
Gokulapriyan/convnext-tiny-224-finetuned-main-gpu-20e-final |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# convnext-tiny-224-finetuned-main-gpu-20e-final
This model is a fine-tuned version of [facebook/convnext-tiny-224](https://huggin... | [
"fnh",
"hcc",
"hem",
"healthy"
] |
bazudde/potato_model |
# Model Trained Using AutoTrain
- Problem type: Multi-class Classification
- Model ID: 44552112263
- CO2 Emissions (in grams): 0.2586
## Validation Metrics
- Loss: 0.098
- Accuracy: 0.923
- Macro F1: 0.911
- Micro F1: 0.923
- Weighted F1: 0.918
- Macro Precision: 0.958
- Micro Precision: 0.923
- Weighted Precision:... | [
"leaf rust",
"root rot",
"alternaria_sweet_potato_leaf_spot"
] |
platzi/platzi-vit |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# platzi-vit
This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patc... | [
"angular_leaf_spot",
"bean_rust",
"healthy"
] |
Gokulapriyan/vit-base-patch16-224-finetuned-main-gpu-20e-final |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# vit-base-patch16-224-finetuned-main-gpu-20e-final
This model is a fine-tuned version of [google/vit-base-patch16-224](https://hu... | [
"fnh",
"hcc",
"hem",
"healthy"
] |
AnneMarie1/swin-tiny-patch4-window7-224-finetuned-fruits-360 |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# swin-tiny-patch4-window7-224-finetuned-fruits-360
This model is a fine-tuned version of [microsoft/swin-tiny-patch4-window7-224]... | [
"apple_6",
"apple_braeburn_1",
"apple_crimson_snow_1",
"apple_golden_1",
"apple_golden_2",
"apple_golden_3",
"apple_granny_smith_1",
"apple_hit_1",
"apple_pink_lady_1",
"apple_red_1",
"apple_red_2",
"apple_red_3",
"apple_red_delicios_1",
"apple_red_yellow_1",
"apple_rotten_1",
"cabbage... |
AnneMarie1/clip-vit-large-patch14-finetuned-fruits-360_vitlarge |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# clip-vit-large-patch14-finetuned-fruits-360_vitlarge
This model is a fine-tuned version of [openai/clip-vit-large-patch14](https... | [
"apple_6",
"apple_braeburn_1",
"apple_crimson_snow_1",
"apple_golden_1",
"apple_golden_2",
"apple_golden_3",
"apple_granny_smith_1",
"apple_hit_1",
"apple_pink_lady_1",
"apple_red_1",
"apple_red_2",
"apple_red_3",
"apple_red_delicios_1",
"apple_red_yellow_1",
"apple_rotten_1",
"cabbage... |
dengcn/vit-base-patch16-224-finetuned-flower |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# vit-base-patch16-224-finetuned-flower
This model is a fine-tuned version of [google/vit-base-patch16-224](https://huggingface.co... | [
"daisy",
"dandelion",
"roses",
"sunflowers",
"tulips"
] |
Casesar/bysz | 1222222222222222 | [
"background",
"tench, tinca tinca",
"goldfish, carassius auratus",
"great white shark, white shark, man-eater, man-eating shark, carcharodon carcharias",
"tiger shark, galeocerdo cuvieri",
"hammerhead, hammerhead shark",
"electric ray, crampfish, numbfish, torpedo",
"stingray",
"cock",
"hen",
"o... |
petrznel/face_discriminator-2 |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# face_discriminator-2
This model is a fine-tuned version of [microsoft/resnet-50](https://huggingface.co/microsoft/resnet-50) on ... | [
"ffhq_res256",
"sd_aligned"
] |
OttoYu/Tree-HK |
## Validation Metrics
- Loss: 0.031
- Accuracy: 1.000
- Macro F1: 1.000
- Micro F1: 1.000
- Weighted F1: 1.000
- Macro Precision: 1.000
- Micro Precision: 1.000
- Weighted Precision: 1.000
- Macro Recall: 1.000
- Micro Recall: 1.000
- Weighted Recall: 1.000 | [
"acacia auriculiformis 耳果相思",
"acacia confusa merr. 台灣相思",
"callistemon rigidus r. br 紅千層",
"callistemon viminalis 串錢柳",
"cinnamomum burmannii 陰香",
"cinnamomum camphora 樟樹",
"crateva trifoliata 鈍葉魚木 ",
"crateva unilocularis 樹頭菜",
"delonix regia 鳳凰木",
"elaeocarpus hainanensis oliv 水石榕",
"elaeocar... |
platzi/platzi-vit-model-gabriel-ichcanziho |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# platzi-vit-model-gabriel-ichcanziho
This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingfac... | [
"angular_leaf_spot",
"bean_rust",
"healthy"
] |
wizofavalon/vit-base-patch16-224-finetuned-flower |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# vit-base-patch16-224-finetuned-flower
This model is a fine-tuned version of [google/vit-base-patch16-224](https://huggingface.co... | [
"daisy",
"dandelion",
"roses",
"sunflowers",
"tulips"
] |
Gustav0/vit-model-Gustav0 |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# vit-model-Gustav0
This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-ba... | [
"angular_leaf_spot",
"bean_rust",
"healthy"
] |
billster45/autotrain-cat_dog-46040114726 |
# Model Trained Using AutoTrain
- Problem type: Binary Classification
- Model ID: 46040114726
- CO2 Emissions (in grams): 1.0946
## Validation Metrics
- Loss: 0.001
- Accuracy: 1.000
- Precision: 1.000
- Recall: 1.000
- AUC: 1.000
- F1: 1.000 | [
"cats",
"dogs"
] |
chbh7051/driver-drowsiness-detection |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# vit-base-driver-drowsiness-detection
This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingfa... | [
"notdrowsy",
"drowsy"
] |
jlara6/platzi-vit-model-jl |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# platzi-vit-model-jl
This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-... | [
"angular_leaf_spot",
"bean_rust",
"healthy"
] |
Snarci/SwinV2-Chaoyang | # Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
This modelcard aims to be a base template for new models. It has been generated using [this raw template](https://github.com/huggingface/huggingface_hub/blob/main/src/huggingface_hub/templates/modelcard_template.md?plain=1).
## Mod... | [
"normal",
"serrated",
"adenocarcinoma",
"adenoma"
] |
linkanjarad/mobilenet_v2_1.0_224-plant-disease-identification |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# mobilenet_v2_1.0_224-plant-disease-identification
This model is a fine-tuned version of [google/mobilenet_v2_1.0_224](https://hu... | [
"apple scab",
"apple with black rot",
"cedar apple rust",
"healthy apple",
"healthy blueberry plant",
"cherry with powdery mildew",
"healthy cherry plant",
"corn (maize) with cercospora and gray leaf spot",
"corn (maize) with common rust",
"corn (maize) with northern leaf blight",
"healthy corn ... |
EugenioRoma/vit_model |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# vit_model
This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch... | [
"angular_leaf_spot",
"bean_rust",
"healthy"
] |
shubhangikarade/vit-base-beans |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# vit-base-beans
This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-... | [
"angular_leaf_spot",
"bean_rust",
"healthy"
] |
Snarci/ViT-base-patch16-384-Chaoyang-finetuned |
# Vision Transformer (base-sized model)
Vision Transformer (ViT) model pre-trained on ImageNet-21k (14 million images, 21,843 classes) at resolution 224x224, and fine-tuned on ImageNet 2012 (1 million images, 1,000 classes) at resolution 384x384. It was introduced in the paper [An Image is Worth 16x16 Words: Transfo... | [
"normal",
"serrated",
"adenocarcinoma",
"adenoma"
] |
Jiajing/my_awesome_food_model |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# my_awesome_food_model
This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vi... | [
"black-grass",
"charlock",
"small-flowered cranesbill",
"sugar beet",
"cleavers",
"common chickweed",
"common wheat",
"fat hen",
"loose silky-bent",
"maize",
"scentless mayweed",
"shepherds purse"
] |
je1lee/my_awesome_food_model |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# my_awesome_food_model
This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vi... | [
"apple_pie",
"baby_back_ribs",
"bruschetta",
"waffles",
"caesar_salad",
"cannoli",
"caprese_salad",
"carrot_cake",
"ceviche",
"cheesecake",
"cheese_plate",
"chicken_curry",
"chicken_quesadilla",
"baklava",
"chicken_wings",
"chocolate_cake",
"chocolate_mousse",
"churros",
"clam_ch... |
Jiajing/SL_final_model |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# SL_final_model
This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-... | [
"black-grass",
"charlock",
"small-flowered cranesbill",
"sugar beet",
"cleavers",
"common chickweed",
"common wheat",
"fat hen",
"loose silky-bent",
"maize",
"scentless mayweed",
"shepherds purse"
] |
sarikaK/vit-base-patch16-224-finetuned-flower |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# vit-base-patch16-224-finetuned-flower
This model is a fine-tuned version of [google/vit-base-patch16-224](https://huggingface.co... | [
"daisy",
"dandelion",
"roses",
"sunflowers",
"tulips"
] |
mavourin/swin-tiny-patch4-window7-224-finetuned-eurosat |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# swin-tiny-patch4-window7-224-finetuned-eurosat
This model is a fine-tuned version of [microsoft/swin-tiny-patch4-window7-224](ht... | [
"fail",
"non"
] |
TariqJamil/vit-base-patch16-224-in21k-handsActDetect |
<!-- This model card has been generated automatically according to the information Keras had access to. You should
probably proofread and complete it, then remove this comment. -->
# TariqJamil/vit-base-patch16-224-in21k-handsActDetect
This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https:/... | [
"thumbs_up",
"stop_gesture",
"right_swipe",
"thumbs_down",
"left_swipe"
] |
ahmedghali/vit-base-patch16-224-finetuned-flower |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# vit-base-patch16-224-finetuned-flower
This model is a fine-tuned version of [google/vit-base-patch16-224](https://huggingface.co... | [
"daisy",
"dandelion",
"roses",
"sunflowers",
"tulips"
] |
platzi/platzi-vit-model-nelson-silvera |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# platzi-vit-model-nelson-silvera
This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co... | [
"angular_leaf_spot",
"bean_rust",
"healthy"
] |
tcvrishank/histo_train_deit |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# histo_train_deit
This model is a fine-tuned version of [facebook/deit-base-distilled-patch16-224](https://huggingface.co/faceboo... | [
"benign",
"insitu",
"invasive",
"normal"
] |
amjadfqs/swin-base-patch4-window7-224-in22k-finetuned-brain-tumor-skullStrippded |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# swin-base-patch4-window7-224-in22k-finetuned-brain-tumor-skullStrippded
This model is a fine-tuned version of [microsoft/swin-ba... | [
"glioma",
"meningioma",
"notumor",
"pituitary"
] |
amjadfqs/swin-base-patch4-window7-224-in22k-finetuned-brain-tumor-skullStrippded_02 |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# swin-base-patch4-window7-224-in22k-finetuned-brain-tumor-skullStrippded_02
This model is a fine-tuned version of [microsoft/swin... | [
"glioma",
"meningioma",
"notumor",
"pituitary"
] |
amjadfqs/swin-base-patch4-window7-224-in22k-finetuned-brain-tumor-skullStrippded_03 |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# swin-base-patch4-window7-224-in22k-finetuned-brain-tumor-skullStrippded_03
This model is a fine-tuned version of [microsoft/swin... | [
"glioma",
"meningioma",
"notumor",
"pituitary"
] |
cledoux42/Ethnicity_Test_v003 |
# Model Trained Using AutoTrain
- Problem type: Multi-class Classification
- Model ID: 47959117029
- CO2 Emissions (in grams): 6.0228
## Validation Metrics
- Loss: 0.530
- Accuracy: 0.796
- Macro F1: 0.797
- Micro F1: 0.796
- Weighted F1: 0.796
- Macro Precision: 0.797
- Micro Precision: 0.796
- Weighted Precision:... | [
"african",
"asian",
"caucasian",
"hispanic",
"indian"
] |
platzi/platzi-vit-model-mewita |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# platzi-vit-model-mewita
This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/... | [
"angular_leaf_spot",
"bean_rust",
"healthy"
] |
sakethchalla/my_isl_model |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# my_isl_model
This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-pa... | [
"a",
"b",
"m",
"n",
"o",
"p",
"q",
"r",
"s",
"t",
"u",
"v",
"c",
"w",
"x",
"y",
"z",
"d",
"e",
"f",
"g",
"i",
"k",
"l"
] |
youngp5/eyeglasses_detection | # Eye Glasses Detection
The model is aimed to detect whether there is any eyeglass in an image. | [
"glasses",
"no%20glasses"
] |
Kartik14Singh/Har_Finetuned-ViT-Hybrid |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# Har_Finetuned-ViT-Hybrid
This model is a fine-tuned version of [google/vit-hybrid-base-bit-384](https://huggingface.co/google/vi... | [
"calling",
"clapping",
"cycling",
"dancing",
"drinking",
"eating",
"fighting",
"hugging",
"laughing",
"listening_to_music",
"running",
"sitting",
"sleeping",
"texting",
"using_laptop"
] |
Kartik14Singh/Har_Finetuned-ViT-Hybrid_ |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# Har_Finetuned-ViT-Hybrid_
This model is a fine-tuned version of [google/vit-hybrid-base-bit-384](https://huggingface.co/google/v... | [
"calling",
"clapping",
"cycling",
"dancing",
"drinking",
"eating",
"fighting",
"hugging",
"laughing",
"listening_to_music",
"running",
"sitting",
"sleeping",
"texting",
"using_laptop"
] |
chanelcolgate/vit-base-patch16-224-chest-x-ray |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# vit-base-patch16-224-chest-x-ray
This model is a fine-tuned version of [google/vit-base-patch16-224](https://huggingface.co/goog... | [
"normal",
"pneumonia"
] |
sakethchalla/isl-nodel |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# isl-nodel
This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch... | [
"a",
"b",
"m",
"n",
"o",
"p",
"q",
"r",
"s",
"t",
"u",
"v",
"c",
"w",
"x",
"y",
"z",
"d",
"e",
"f",
"g",
"i",
"k",
"l"
] |
amjadfqs/swin-base-patch4-window7-224-in22k-finetuned-brain-tumor-skullStrippded_04 |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# swin-base-patch4-window7-224-in22k-finetuned-brain-tumor-skullStrippded_04
This model is a fine-tuned version of [microsoft/swin... | [
"glioma",
"meningioma",
"notumor",
"pituitary"
] |
adamtky/vit-base-patch16-224-finetuned-flower |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# vit-base-patch16-224-finetuned-flower
This model is a fine-tuned version of [google/vit-base-patch16-224](https://huggingface.co... | [
"daisy",
"dandelion",
"roses",
"sunflowers",
"tulips"
] |
dingzhaohan/swin-tiny-patch4-window7-224-finetuned-eurosat-kornia |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# swin-tiny-patch4-window7-224-finetuned-eurosat-kornia
This model is a fine-tuned version of [microsoft/swin-tiny-patch4-window7-... | [
"annualcrop",
"forest",
"herbaceousvegetation",
"highway",
"industrial",
"pasture",
"permanentcrop",
"residential",
"river",
"sealake"
] |
jmrv002/vit-model-jmrv002 |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# vit-model-jmrv002
This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-ba... | [
"angular_leaf_spot",
"bean_rust",
"healthy"
] |
willmendoza/platzi-vit-model-will-mendoza |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# platzi-vit-model-will-mendoza
This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/g... | [
"angular_leaf_spot",
"bean_rust",
"healthy"
] |
CHXXX249/swin-tiny-patch4-window7-224-finetuned-eurosat |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# swin-tiny-patch4-window7-224-finetuned-eurosat
This model is a fine-tuned version of [microsoft/swin-tiny-patch4-window7-224](ht... | [
"annualcrop",
"forest",
"herbaceousvegetation",
"highway",
"industrial",
"pasture",
"permanentcrop",
"residential",
"river",
"sealake"
] |
Gokulapriyan/deit-tiny-patch16-224-finetuned-main-gpu-20e-final |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# deit-tiny-patch16-224-finetuned-main-gpu-20e-final
This model is a fine-tuned version of [facebook/deit-tiny-patch16-224](https:... | [
"fnh",
"hcc",
"hem",
"healthy"
] |
machves/Clasificacion-vit-model-manuel-chaves |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# Clasificacion-vit-model-manuel-chaves
This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingf... | [
"angular_leaf_spot",
"bean_rust",
"healthy"
] |
fufufukakaka/pokemon_image_classifier |
ポケモンの選出画面での画像を入力として、そのポケモンを識別するモデルです。
`microsoft/swin-base-patch4-window7-224-in22k` を元にして fine-tuning しています。
Repo: https://github.com/fufufukakaka/poke_battle_logger | [
"へイラッシャ",
"アグノム",
"アシレーヌ",
"アブリボン",
"アマージョ",
"アメモース",
"アラブルタケ",
"アローラキュウコン",
"アローラゴローニャ",
"アローラベトベトン",
"アーマーガア",
"イイネイヌ",
"イエッサン",
"イキリンコ",
"イダイトウ・オス",
"イダイトウ・メス",
"イダイナキバ",
"イッカネズミ",
"イルカマン",
"イーユイ",
"ウインディ",
"ウェーニバル",
"ウォッシュロトム",
"ウガツホムラ",
"ウッウ",
"ウネルミナモ",
"ウルガモ... |
friesel/autotrain-tarkov_images_reduced_i-48889118357 |
# Model Trained Using AutoTrain
- Problem type: Multi-class Classification
- Model ID: 48889118357
- CO2 Emissions (in grams): 1.4021
## Validation Metrics
- Loss: 0.038
- Accuracy: 0.986
- Macro F1: 0.977
- Micro F1: 0.986
- Weighted F1: 0.986
- Macro Precision: 0.980
- Micro Precision: 0.986
- Weighted Precision:... | [
"5a0abb6e1526d8000a025282-512",
"5a0c27731526d80618476ac4-512",
"5a0eb38b86f774153b320eb0-512",
"5a0eb6ac86f7743124037a28-512",
"5a0eb980fcdbcb001a3b00a6-512",
"5a0ec13bfcdbcb00165aa685-512",
"5a0ec6d286f7742c0b518fb5-512",
"5a0ec70e86f7742c0b518fba-512",
"5a0ed824fcdbcb0176308b0d-512",
"5a0ee3078... |
friesel/autotrain-tarkov_images_reduced_i-48889118355 |
# Model Trained Using AutoTrain
- Problem type: Multi-class Classification
- Model ID: 48889118355
- CO2 Emissions (in grams): 0.0130
## Validation Metrics
- Loss: 0.039
- Accuracy: 1.000
- Macro F1: 1.000
- Micro F1: 1.000
- Weighted F1: 1.000
- Macro Precision: 1.000
- Micro Precision: 1.000
- Weighted Precision:... | [
"5a0abb6e1526d8000a025282-512",
"5a0c27731526d80618476ac4-512",
"5a0eb38b86f774153b320eb0-512",
"5a0eb6ac86f7743124037a28-512",
"5a0eb980fcdbcb001a3b00a6-512",
"5a0ec13bfcdbcb00165aa685-512",
"5a0ec6d286f7742c0b518fb5-512",
"5a0ec70e86f7742c0b518fba-512",
"5a0ed824fcdbcb0176308b0d-512",
"5a0ee3078... |
priyankloco/swin-base-patch4-window7-224-in22k-finetuned_swinv1-all-classes-autotags-latest |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# swin-base-patch4-window7-224-in22k-finetuned_swinv1-all-classes-autotags-latest
This model is a fine-tuned version of [microsoft... | [
"accordion",
"button",
"cards",
"checkbox",
"date-time",
"dropdown_closed",
"form",
"input",
"multi-node_horizontal",
"multi-node_vertical",
"progress_circular",
"progress_linear",
"progress_stepper",
"radio",
"sections",
"slider",
"switch",
"text-area"
] |
Gokulapriyan/vit-base-patch16-224-finetuned-main-gpu-20e-final-1 |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# vit-base-patch16-224-finetuned-main-gpu-20e-final-1
This model is a fine-tuned version of [google/vit-base-patch16-224](https://... | [
"fnh",
"hcc",
"hem",
"healthy"
] |
AiBototicus/autotrain-colors-1-49130118878 |
# Model Trained Using AutoTrain
- Problem type: Multi-class Classification
- Model ID: 49130118878
- CO2 Emissions (in grams): 0.1906
## Validation Metrics
- Loss: 0.384
- Accuracy: 1.000
- Macro F1: 1.000
- Micro F1: 1.000
- Weighted F1: 1.000
- Macro Precision: 1.000
- Micro Precision: 1.000
- Weighted Precision:... | [
"blue",
"green",
"red"
] |
priyankloco/resnet-101-finetuned_resnet101-all-classes-autotags |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# resnet-101-finetuned_resnet101-all-classes-autotags
This model is a fine-tuned version of [microsoft/resnet-101](https://hugging... | [
"accordion",
"black",
"button",
"cards",
"checkbox",
"date-time",
"dropdown_closed",
"form",
"input",
"multi-node_horizontal",
"multi-node_vertical",
"progress_circular",
"progress_linear",
"progress_stepper",
"radio",
"sections",
"slider",
"switch",
"text-area",
"white"
] |
priyankloco/resnet-101-finetuned_resnet101-cnn-autotags |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# resnet-101-finetuned_resnet101-cnn-autotags
This model is a fine-tuned version of [microsoft/resnet-101](https://huggingface.co/... | [
"accordion",
"black",
"button",
"cards",
"checkbox",
"date-time",
"dropdown_closed",
"form",
"input",
"multi-node_horizontal",
"multi-node_vertical",
"progress_circular",
"progress_linear",
"progress_stepper",
"radio",
"sections",
"slider",
"switch",
"text-area",
"white"
] |
rafferty/autotrain-amber-mine-tutorial |
# Model Trained Using AutoTrain
- Problem type: Binary Classification
- Model ID: 49296119123
- CO2 Emissions (in grams): 0.3929
## Validation Metrics
- Loss: 0.107
- Accuracy: 0.980
- Precision: 0.962
- Recall: 1.000
- AUC: 0.995
- F1: 0.980 | [
"negative",
"positive"
] |
platzi/platzi-vit-model-rob-vilchis |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# platzi-vit-model-rob-vilchis
This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/go... | [
"angular_leaf_spot",
"bean_rust",
"healthy"
] |
farantes/autotrain-receipt-classification-49332119193 |
# Model Trained Using AutoTrain
- Problem type: Multi-class Classification
- Model ID: 49332119193
- CO2 Emissions (in grams): 0.3126
## Validation Metrics
- Loss: 0.019
- Accuracy: 1.000
- Macro F1: 1.000
- Micro F1: 1.000
- Weighted F1: 1.000
- Macro Precision: 1.000
- Micro Precision: 1.000
- Weighted Precision:... | [
"doclike",
"luggagelike",
"notreceiptlike",
"receiptlike"
] |
priyankloco/resnet-101-finetuned_resnet101-sgd-optimizer-autotags |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# resnet-101-finetuned_resnet101-sgd-optimizer-autotags
This model is a fine-tuned version of [microsoft/resnet-101](https://huggi... | [
"accordion",
"black",
"button",
"cards",
"checkbox",
"date-time",
"dropdown_closed",
"form",
"input",
"multi-node_horizontal",
"multi-node_vertical",
"progress_circular",
"progress_linear",
"progress_stepper",
"radio",
"sections",
"slider",
"switch",
"text-area",
"white"
] |
MBZUAI/swiftformer-xs |
# SwiftFormer (swiftformer-xs)
## Model description
The SwiftFormer model was proposed in [SwiftFormer: Efficient Additive Attention for Transformer-based Real-time Mobile Vision Applications](https://arxiv.org/abs/2303.15446) by Abdelrahman Shaker, Muhammad Maaz, Hanoona Rasheed, Salman Khan, Ming-Hsuan Yang, Fahad... | [
"tench, tinca tinca",
"goldfish, carassius auratus",
"great white shark, white shark, man-eater, man-eating shark, carcharodon carcharias",
"tiger shark, galeocerdo cuvieri",
"hammerhead, hammerhead shark",
"electric ray, crampfish, numbfish, torpedo",
"stingray",
"cock",
"hen",
"ostrich, struthio... |
priyankloco/resnet-101-finetuned_resnet101-sgd-optimizer20-autotags |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# resnet-101-finetuned_resnet101-sgd-optimizer20-autotags
This model is a fine-tuned version of [microsoft/resnet-101](https://hug... | [
"accordion",
"black",
"button",
"cards",
"checkbox",
"date-time",
"dropdown_closed",
"form",
"input",
"multi-node_horizontal",
"multi-node_vertical",
"progress_circular",
"progress_linear",
"progress_stepper",
"radio",
"sections",
"slider",
"switch",
"text-area",
"white"
] |
priyankloco/resnet-101-finetuned_resnet101-adam-optimizer5e-4-autotags |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# resnet-101-finetuned_resnet101-adam-optimizer5e-4-autotags
This model is a fine-tuned version of [microsoft/resnet-101](https://... | [
"accordion",
"black",
"button",
"cards",
"checkbox",
"date-time",
"dropdown_closed",
"form",
"input",
"multi-node_horizontal",
"multi-node_vertical",
"progress_circular",
"progress_linear",
"progress_stepper",
"radio",
"sections",
"slider",
"switch",
"text-area",
"white"
] |
priyankloco/resnet-152-finetuned_resnet152-adam-optimizer5e-4-autotags |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# resnet-152-finetuned_resnet152-adam-optimizer5e-4-autotags
This model is a fine-tuned version of [microsoft/resnet-152](https://... | [
"accordion",
"black",
"button",
"cards",
"checkbox",
"date-time",
"dropdown_closed",
"form",
"input",
"multi-node_horizontal",
"multi-node_vertical",
"progress_circular",
"progress_linear",
"progress_stepper",
"radio",
"sections",
"slider",
"switch",
"text-area",
"white"
] |
priyankloco/resnet-152-finetuned_resnet152-adam-optimizere-2-autotags |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# resnet-152-finetuned_resnet152-adam-optimizere-2-autotags
This model is a fine-tuned version of [microsoft/resnet-152](https://h... | [
"accordion",
"black",
"button",
"cards",
"checkbox",
"date-time",
"dropdown_closed",
"form",
"input",
"multi-node_horizontal",
"multi-node_vertical",
"progress_circular",
"progress_linear",
"progress_stepper",
"radio",
"sections",
"slider",
"switch",
"text-area",
"white"
] |
tcvrishank/histo_train_resnet |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# histo_train_resnet
This model is a fine-tuned version of [microsoft/resnet-50](https://huggingface.co/microsoft/resnet-50) on th... | [
"benign",
"insitu",
"invasive",
"normal"
] |
carolinetfls/plant-seedlings-model |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# plant-seedlings-model
This model is a fine-tuned version of [google/vit-base-patch16-224](https://huggingface.co/google/vit-base... | [
"black-grass",
"charlock",
"small-flowered cranesbill",
"sugar beet",
"cleavers",
"common chickweed",
"common wheat",
"fat hen",
"loose silky-bent",
"maize",
"scentless mayweed",
"shepherds purse"
] |
Soulaimen/swin-tiny-patch4-window7-224-finetuned-eurosat |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# swin-tiny-patch4-window7-224-finetuned-eurosat
This model is a fine-tuned version of [microsoft/swin-tiny-patch4-window7-224](ht... | [
"chemise",
"hoodies"
] |
hn11235/SL_final_model |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# SL_final_model
This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-... | [
"black-grass",
"charlock",
"small-flowered cranesbill",
"sugar beet",
"cleavers",
"common chickweed",
"common wheat",
"fat hen",
"loose silky-bent",
"maize",
"scentless mayweed",
"shepherds purse"
] |
carolinetfls/plant-seedlings-model-ConvNet |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# plant-seedlings-model-ConvNet
This model is a fine-tuned version of [facebook/convnext-tiny-224](https://huggingface.co/facebook... | [
"black-grass",
"charlock",
"small-flowered cranesbill",
"sugar beet",
"cleavers",
"common chickweed",
"common wheat",
"fat hen",
"loose silky-bent",
"maize",
"scentless mayweed",
"shepherds purse"
] |
Dewa/dog_emotion_v2 | # Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
This model is intended to detect emotion of a 🐕dog by its 📸image
## Model Details
Model is fine-tunned using kaggle-dog-emotion-dataset
It classify the dog's emotion into .😔sad,😀happy,😡angry,😌relaxed.
sometime machine can ... | [
"sad",
"angry",
"happy",
"relaxed"
] |
sakethchalla/isl-model |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# isl-model
This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch... | [
"a",
"b",
"m",
"n",
"o",
"p",
"q",
"r",
"s",
"t",
"u",
"v",
"c",
"w",
"x",
"y",
"z",
"d",
"e",
"f",
"g",
"i",
"k",
"l"
] |
sammyboi1801/vit-base-lfw-face |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# vit-base-lfw-face
This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-ba... | [
"abdullah_gul",
"adrien_brody",
"ari_fleischer",
"nancy_pelosi",
"naomi_watts",
"nestor_kirchner",
"nicanor_duarte_frutos",
"nicole_kidman",
"norah_jones",
"paul_bremer",
"paul_burrell",
"pervez_musharraf",
"pete_sampras",
"ariel_sharon",
"pierce_brosnan",
"queen_elizabeth_ii",
"rece... |
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