Model Zoo - PyTorch¶
The RBLN PyTorch Model Zoo offers a wide variety of neural network models designed to run on the RBLN NPU. The number of models covered by the RBLN Model Zoo will continuously expand as the RBLN SDK is upated. You can access full list of the models in the RBLN Model Zoo GitHub repository.
Supported models¶
Here is the full list of the models covered by the RBLN PyTorch Model Zoo as of today.
| Model | Dataset | Task |
|---|---|---|
| Stable Diffusion v1.5 | LAION-2B | |
| Stable Diffusion XL | - | |
| SDXL-turbo | - | |
| ControlNet | - | |
| Llama3-8b | A new mix of publicly available online data | Text Generation |
| Llama2-7b | A new mix of publicly available online data | Text Generation |
| Llama2-13b | A new mix of publicly available online data | Text Generation |
| Phi-2 | 250B tokens, combination of NLP synthetic data created by AIOAI GPT-3.5 | Text Generation |
| Gemma-7b | 6 trillion tokens of web, code, and mathematics text | Text Generation |
| Gemma-2b | 6 trillion tokens of web, code, and mathematics text | Text Generation |
| Mistral-7b | Publicly available online data | Text Generation |
| Qwen2-7b | 7T tokens of internal data | Text Generation |
| Salamandra-7b | 2.4T tokens of 35 European languages and 92 programming languages | Text Generation |
| EXAONE-3.0-7.8b | 8T tokens of curated English and Korean data | Text Generation |
| Mi:dm-7b | AI-HUB/the National Institute of Korean Language | Text Generation |
| GPT2 | WebText | Text Generation |
| GPT2-medium | WebText | Text Generation |
| GPT2-large | WebText | Text Generation |
| GPT2-xl | WebText | Text Generation |
| SOLAR-10.7b | alpaca-gpt4-data + etc. | Text Generation |
| EEVE-Korean-10.8b | Korean-translated ver. of Open-Orca/SlimOrca-Dedup and argilla/ultrafeedback-binarized-preferences-cleaned | Text Generation |
| Llava-v1.6-mistral-7b | - | Image Captioning |
| T5-small | Colossal Clean Crawled Corpus | Text Generation |
| T5-base | Colossal Clean Crawled Corpus | Text Generation |
| T5-large | Colossal Clean Crawled Corpus | Text Generation |
| T5-3b | Colossal Clean Crawled Corpus | Text Generation |
| BART-base | BookCorpus + etc. | Text Generation |
| BART-large | BookCorpus + etc. | Text Generation |
| KoBART-base | Korean Wiki | Text Generation |
| E5-base-4K | Colossal Clean text Pairs | Embedding Retrieval |
| BERT-base | - BookCorpus & English Wikipedia - SQuAD v2 |
|
| BERT-large | - BookCorpus & English Wikipedia - SQuAD v2 |
|
| DistilBERT-base | - BookCorpus & English Wikipedia - SQuAD v2 |
Question Answering |
| SecureBERT | a manually crafted dataset from the human readable descriptions of MITRE ATT&CK techniques and tactics | Masked Langague Modeling |
| RoBERTa | a manually crafted dataset from the human readable descriptions of MITRE ATT&CK techniques and tactics | Text Classification |
| MotionBERT | - Human3.6M & AMASS - NTURGB+D |
|
| BGE-M3 | MLDR and bge-m3-data | Embedding Retrieval |
| BGE-Reranker-V2-M3 | MLDR and bge-m3-data | Embedding Retrieval |
| BGE-Reranker-Base | MLDR and bge-m3-data | Embedding Retrieval |
| BGE-Reranker-Large | MLDR and bge-m3-data | Embedding Retrieval |
| BLIP2-2.7b | LAION | Image Captioning |
| Whisper-tiny | 680k hours of labeled data from the web | Speech to Text |
| Whisper-base | 680k hours of labeled data from the web | Speech to Text |
| Whisper-small | 680k hours of labeled data from the web | Speech to Text |
| Whisper-medium | 680k hours of labeled data from the web | Speech to Text |
| Whisper-large-v3 | 680k hours of labeled data from the web | Speech to Text |
| Whisper-large-v3-turbo | 680k hours of labeled data from the web | Speech to Text |
| Wav2Vec2 | Librispeech | Speech to Text |
| ConvTasNet | WSJ | Speech Separation |
| Audio-Spectogram-Transformer | AudioSet | Audio Classification |
| Time-Series-Transformer | tourism-monthly dataset | Time-series Forecasting |
| DPT-large | MIX 6 | Monocular Depth Estimation |
| SAM2.1_hiera_large | SA-V | Semantic Segmentation |
| DeepLabV3_ResNet50 | ILSVRC2012 | Semantic Segmentation |
| DeepLabV3_ResNet101 | ILSVRC2012 | Semantic Segmentation |
| DeepLabV3_MobileNetV3_Large | ILSVRC2012 | Semantic Segmentation |
| FCN_ResNet50 | ILSVRC2012 | Semantic Segmentation |
| FCN_ResNet101 | ILSVRC2012 | Semantic Segmentation |
| UNet | Carvana | Semantic Segmentation |
| ViT-large | ImageNet-21k & ImageNet | Image Classification |
| DeiT-tiny | ILSVRC2012 | Image Classification |
| DeiT-tiny distilled | ILSVRC2012 | Image Classification |
| DeiT-small | ILSVRC2012 | Image Classification |
| DeiT-small distilled | ILSVRC2012 | Image Classification |
| DeiT-base | ILSVRC2012 | Image Classification |
| DeiT-base distilled | ILSVRC2012 | Image Classification |
| DeiT-base 384 | ILSVRC2012 | Image Classification |
| DeiT-base distilled 384 | ILSVRC2012 | Image Classification |
| R3D_18 | KINETICS400_V1 | Video Classification |
| MC3_18 | KINETICS400_V1 | Video Classification |
| R(2+1)D_18 | KINETICS400_V1 | Video Classification |
| S3D | KINETICS400_V1 | Video Classification |
| YOLOv3-tiny | COCO | Obejct Detection |
| YOLOv3 | COCO | Obejct Detection |
| YOLOv3-spp | COCO | Obejct Detection |
| YOLOv4 | COCO | Obejct Detection |
| YOLOv4-csp-s-mish | COCO | Obejct Detection |
| YOLOv4-csp-x-mish | COCO | Obejct Detection |
| YOLOv5n | COCO | Obejct Detection |
| YOLOv5s | COCO | Obejct Detection |
| YOLOv5m | COCO | Obejct Detection |
| YOLOv5l | COCO | Obejct Detection |
| YOLOv5x | COCO | Obejct Detection |
| YOLOv6s | COCO | Obejct Detection |
| YOLOv6n | COCO | Obejct Detection |
| YOLOv6m | COCO | Obejct Detection |
| YOLOv6l | COCO | Obejct Detection |
| YOLOv7-tiny | COCO | Obejct Detection |
| YOLOv7 | COCO | Obejct Detection |
| YOLOv7x | COCO | Obejct Detection |
| YOLOv8n | COCO | Obejct Detection |
| YOLOv8s | COCO | Obejct Detection |
| YOLOv8n | COCO | Obejct Detection |
| YOLOv8m | COCO | Obejct Detection |
| YOLOv8l | COCO | Obejct Detection |
| YOLOv8x | COCO | Obejct Detection |
| YOLOX-nano | COCO | Obejct Detection |
| YOLOX-tiny | COCO | Obejct Detection |
| YOLOX-s | COCO | Obejct Detection |
| YOLOX-m | COCO | Obejct Detection |
| YOLOX-l | COCO | Obejct Detection |
| YOLOX-x | COCO | Obejct Detection |
| YOLOX-darknet53 | COCO | Obejct Detection |
| 3DDFA_V2 | 300W-LP | Face Alignment |
| ConvNeXtTiny | ILSVRC2012 | Image Classification |
| ConvNeXtSmall | ILSVRC2012 | Image Classification |
| ConvNeXtBase | ILSVRC2012 | Image Classification |
| ConvNeXtLarge | ILSVRC2012 | Image Classification |
| EfficientNetB0 | ILSVRC2012 | Image Classification |
| EfficientNetB1 | ILSVRC2012 | Image Classification |
| EfficientNetB2 | ILSVRC2012 | Image Classification |
| EfficientNetB3 | ILSVRC2012 | Image Classification |
| EfficientNetB4 | ILSVRC2012 | Image Classification |
| EfficientNetB5 | ILSVRC2012 | Image Classification |
| EfficientNetB6 | ILSVRC2012 | Image Classification |
| EfficientNetB7 | ILSVRC2012 | Image Classification |
| EfficientNet_V2_S | ILSVRC2012 | Image Classification |
| EfficientNet_V2_M | ILSVRC2012 | Image Classification |
| EfficientNet_V2_L | ILSVRC2012 | Image Classification |
| Wide_ResNet50_2 | ILSVRC2012 | Image Classification |
| Wide_ResNet101_2 | ILSVRC2012 | Image Classification |
| MNASNet0_5 | ILSVRC2012 | Image Classification |
| MNASNet0_75 | ILSVRC2012 | Image Classification |
| MNASNet1_0 | ILSVRC2012 | Image Classification |
| MNASNet1_3 | ILSVRC2012 | Image Classification |
| MobileNet_V2 | ILSVRC2012 | Image Classification |
| MobileNet_V3_Small | ILSVRC2012 | Image Classification |
| MobileNet_V3_Large | ILSVRC2012 | Image Classification |
| ResNet18 | ILSVRC2012 | Image Classification |
| ResNet34 | ILSVRC2012 | Image Classification |
| ResNet50 | ILSVRC2012 | Image Classification |
| ResNet101 | ILSVRC2012 | Image Classification |
| ResNet152 | ILSVRC2012 | Image Classification |
| ResNet101V2 | ILSVRC2012 | Image Classification |
| ResNet152V2 | ILSVRC2012 | Image Classification |
| VGG11 | ILSVRC2012 | Image Classification |
| VGG11_BN | ILSVRC2012 | Image Classification |
| VGG13 | ILSVRC2012 | Image Classification |
| VGG13_BN | ILSVRC2012 | Image Classification |
| VGG16 | ILSVRC2012 | Image Classification |
| VGG16_BN | ILSVRC2012 | Image Classification |
| VGG19 | ILSVRC2012 | Image Classification |
| VGG19_BN | ILSVRC2012 | Image Classification |
| SqueezeNet1_0 | ILSVRC2012 | Image Classification |
| SqueezeNet1_1 | ILSVRC2012 | Image Classification |
| ShuffleNet_V2_X0_5 | ILSVRC2012 | Image Classification |
| ShuffleNet_V2_X1_0 | ILSVRC2012 | Image Classification |
| ShuffleNet_V2_X1_5 | ILSVRC2012 | Image Classification |
| ShuffleNet_V2_X2_0 | ILSVRC2012 | Image Classification |
| DenseNet121 | ILSVRC2012 | Image Classification |
| DenseNet161 | ILSVRC2012 | Image Classification |
| DenseNet169 | ILSVRC2012 | Image Classification |
| DenseNet201 | ILSVRC2012 | Image Classification |
| RegNet_X_400MF | ILSVRC2012 | Image Classification |
| RegNet_X_800MF | ILSVRC2012 | Image Classification |
| RegNet_X_1_6GF | ILSVRC2012 | Image Classification |
| RegNet_X_3_2GF | ILSVRC2012 | Image Classification |
| RegNet_X_8GF | ILSVRC2012 | Image Classification |
| RegNet_X_16GF | ILSVRC2012 | Image Classification |
| RegNet_X_32GF | ILSVRC2012 | Image Classification |
| RegNet_Y_400MF | ILSVRC2012 | Image Classification |
| RegNet_Y_800MF | ILSVRC2012 | Image Classification |
| RegNet_Y_1_6GF | ILSVRC2012 | Image Classification |
| RegNet_Y_3_2GF | ILSVRC2012 | Image Classification |
| RegNet_Y_8GF | ILSVRC2012 | Image Classification |
| RegNet_Y_16GF | ILSVRC2012 | Image Classification |
| RegNet_Y_32GF | ILSVRC2012 | Image Classification |
| RegNet_Y_128GF | ILSVRC2012 | Image Classification |
| ResNeXt50_32x4D | ILSVRC2012 | Image Classification |
| ResNeXt101_32x8D | ILSVRC2012 | Image Classification |
| ResNeXt101_64x4D | ILSVRC2012 | Image Classification |
| AlexNet | ILSVRC2012 | Image Classification |
| GoogLeNet | ILSVRC2012 | Image Classification |
| Inception_V3 | ILSVRC2012 | Image Classification |