198
Unit 1 Quiz - AI Agent Fundementals
๐ฅ
Test your knowledge of the Agent fundamentals.
Abdulrahman Al-Ghamdi
Abdu-GH
AI & ML interests
me love NLP
Recent Activity
liked
a Space
22 days ago
agents-course/unit_1_quiz
reacted
to
KaiChen1998's
post
with ๐ฅ
23 days ago
๐ข Our EMOVA paper has been accepted by CVPR 2025, and we are glad to release all resources, including code (training & inference), datasets (training & evaluation), and checkpoints (EMOVA-3B/7B/72B)!
๐ค EMOVA is a novel end-to-end omni-modal LLM that can see, hear and speak. Given omni-modal (i.e., textual, visual and speech) inputs, EMOVA can generate both textual and speech responses with vivid emotional controls by utilizing the speech decoder and a style controller.
โจ EMOVA Highlights
โ
State-of-the-art omni-modality: EMOVA achieves SoTA comparable results on both vision-language and speech benchmarks simultaneously.
โ
Device adaptation: our codebase supports training/inference on both NVIDIA GPUs (e.g., A800 & H20) and Ascend NPUs (e.g., 910B3)!
โ
Modular design: we integrate multiple implementations of vision encoder, vision projector, and language model, even including the most recent DeepSeekMoE-tiny!
๐ฅ You are all welcome to try and star!
- Project page: https://emova-ollm.github.io/
- Github: https://github.com/emova-ollm/EMOVA
- Demo: https://huggingface.co/spaces/Emova-ollm/EMOVA-demo
reacted
to
KaiChen1998's
post
with ๐
23 days ago
๐ข Our EMOVA paper has been accepted by CVPR 2025, and we are glad to release all resources, including code (training & inference), datasets (training & evaluation), and checkpoints (EMOVA-3B/7B/72B)!
๐ค EMOVA is a novel end-to-end omni-modal LLM that can see, hear and speak. Given omni-modal (i.e., textual, visual and speech) inputs, EMOVA can generate both textual and speech responses with vivid emotional controls by utilizing the speech decoder and a style controller.
โจ EMOVA Highlights
โ
State-of-the-art omni-modality: EMOVA achieves SoTA comparable results on both vision-language and speech benchmarks simultaneously.
โ
Device adaptation: our codebase supports training/inference on both NVIDIA GPUs (e.g., A800 & H20) and Ascend NPUs (e.g., 910B3)!
โ
Modular design: we integrate multiple implementations of vision encoder, vision projector, and language model, even including the most recent DeepSeekMoE-tiny!
๐ฅ You are all welcome to try and star!
- Project page: https://emova-ollm.github.io/
- Github: https://github.com/emova-ollm/EMOVA
- Demo: https://huggingface.co/spaces/Emova-ollm/EMOVA-demo
Organizations
None yet
Abdu-GH's activity
liked
a
Space
22 days ago
liked
a
model
about 2 months ago
liked
a
model
2 months ago
liked
a
Space
2 months ago
liked
2
Spaces
3 months ago
liked
a
Space
6 months ago