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Modelbit Model Hub
Browse our library of open source models that are ready to deploy behind an API endpoint in seconds.
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SAM 2
SAM 2 is the first unified model for segmenting objects across images and videos. You can use a click, box, or mask as the input to select an object on any image or frame of video.
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Llama 3.1 8B
Llama 3.1 8B is the smallest variant of Meta AI's state of the art open-source LLM family.
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YOLO v9
YOLO v9 is the latest iteration in the YOLO series, known for its significant advancements in real-time object detection, efficiency, and accuracy.
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CVT
The Convolutional Vision Transformer (CvT) integrates convolutional operations into the transformer architecture, enhancing performance and efficiency in image processing.
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OWLv2
OWLv2 is an advanced machine learning model developed by Google, designed to improve zero-shot object detection.
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LLaVa
LLaVa is a state-of-the-art machine learning model designed for advanced multimodal language and vision understanding.
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Depth Anything
The Depth Anything model is a foundation model for robust monocular depth estimation
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Llama 2-7b
LLaMA 2 7B model is an auto-regressive language model developed by Meta, designed for a variety of natural language processing tasks.
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SeamlessM4T v2
SeamlessM4T v2 is a multimodal machine translation model developed by Meta AI, capable of translating speech and text across multiple languages.
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Detectron 2
Detectron2 is a cutting-edge machine learning model from Meta AI, renowned for its high performance in object detection and segmentation tasks across diverse fields.
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OpenCV
OpenCV offers a range of machine learning models and algorithms for various applications in computer vision.
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DINOv2
Grounding DINO v2 enhances open-set object detection capabilities by integrating DINO's self-supervised learning with grounded pre-training, catering to the detection of both known and unknown objects.
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OpenAI Whisper v3
OpenAI Whisper v3 is a cutting-edge speech recognition model offering enhanced accuracy, multilingual support, and advanced features for efficient speech-to-text conversion.
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AdaBoost
AdaBoost is an ensemble ML algorithm that enhances the performance of weak classifiers to create a strong predictive model.
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ResNet-50
ResNet-50 is a deep learning model known for its novel residual learning framework, significantly impacting computer vision and other domains.
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DistilBERT
DistilBERT is a streamlined version of the BERT model, offering a balance between performance and efficiency for various natural language processing tasks.
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YOLOv8
YOLO v8 is a fast and accurate deep learning model for real-time object detection in images and videos.
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CatBoost
CatBoost is an open-source gradient boosting library from Yandex, known for efficient handling of categorical data.
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LightGBM
LightGBM is a fast, distributed, high-performance gradient boosting framework, used in many winning machine learning competitions.
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Segment Anything Model (SAM)
The Segment Anything Model (SAM) is an advanced machine learning model designed for highly versatile and precise image segmentation across diverse scenarios.
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XGBoost
XGBoost is an optimized distributed gradient boosting library designed for efficiency, flexibility, and portability.
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Model Comparisons
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Models
All Models
SAM 2
Llama 3.1 8B
YOLO v9
CVT
OWLv2
LLaVa
Depth Anything
Llama 2-7b
SeamlessM4T v2
Detectron 2
OpenCV
DINOv2
OpenAI Whisper v3
AdaBoost
ResNet-50
DistilBERT
YOLOv8
CatBoost
LightGBM
Segment Anything Model (SAM)
XGBoost
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