NVlabs/prismer
The implementation of "Prismer: A Vision-Language Model with An Ensemble of Experts".
Language: Python
#image_captioning #language_model #multi_modal_learning #multi_task_learning #vision_and_language #vision_language_model #vqa
Stars: 479 Issues: 6 Forks: 21
https://github.com/NVlabs/prismer
The implementation of "Prismer: A Vision-Language Model with An Ensemble of Experts".
Language: Python
#image_captioning #language_model #multi_modal_learning #multi_task_learning #vision_and_language #vision_language_model #vqa
Stars: 479 Issues: 6 Forks: 21
https://github.com/NVlabs/prismer
GitHub
GitHub - NVlabs/prismer: The implementation of "Prismer: A Vision-Language Model with Multi-Task Experts".
The implementation of "Prismer: A Vision-Language Model with Multi-Task Experts". - NVlabs/prismer
roboflow/multimodal-maestro
Effective prompting for Large Multimodal Models like GPT-4 Vision or LLaVA. 🔥
Language: Python
#cross_modal #gpt_4 #gpt_4_vision #instance_segmentation #llava #lmm #multimodality #object_detection #prompt_engineering #segment_anything #vision_language_model #visual_prompting
Stars: 367 Issues: 1 Forks: 23
https://github.com/roboflow/multimodal-maestro
Effective prompting for Large Multimodal Models like GPT-4 Vision or LLaVA. 🔥
Language: Python
#cross_modal #gpt_4 #gpt_4_vision #instance_segmentation #llava #lmm #multimodality #object_detection #prompt_engineering #segment_anything #vision_language_model #visual_prompting
Stars: 367 Issues: 1 Forks: 23
https://github.com/roboflow/multimodal-maestro
GitHub
GitHub - roboflow/maestro: streamline the fine-tuning process for multimodal models: PaliGemma, Florence-2, and Qwen2-VL
streamline the fine-tuning process for multimodal models: PaliGemma, Florence-2, and Qwen2-VL - roboflow/maestro