thanhkt/test
0 Bytes
Tran Khanh Thanh
thanhkt
AI & ML interests
AI Agents, Robotics
Recent Activity
published a bucket about 1 month ago
thanhkt/test upvoted a paper about 2 months ago
TurboVLA: Real-Time Vision-Language-Action Model at 32 Hz on an RTX 4090 with <1 GB VRAM upvoted an article 2 months ago
LeRobot v0.6.0: Imagine, Evaluate, ImproveOrganizations
published a
bucket about 1 month ago
upvoted a paper about 2 months ago
upvoted an article 2 months ago
Article
LeRobot v0.6.0: Imagine, Evaluate, Improve
- +7
imstevenpmwork, pepijn223, CarolinePascal, lilkm, maximellerbach, nepyope, nikodembartnik, Nico-robot, thomwolf
• • 85 updated a
dataset 3 months ago
authored a
paper 4 months ago
upvoted a paper 4 months ago
liked a
model 6 months ago
published a
dataset 6 months ago
upvoted an article 8 months ago
Article
LightOnOCR-2-1B: a lightweight high-performance end-to-end OCR model family
lightonai
• • 104 upvoted a collection 9 months ago
liked a
Space about 1 year ago
upvoted 2
articles over 1 year ago
Article
Introducing Training Cluster as a Service - a new collaboration with NVIDIA
- +1
jeffboudier, ark393, pagezyhf
• • 27 Article
Model2Vec: Distill a Small Fast Model from any Sentence Transformer
Pringled
• • 105 upvoted a paper over 1 year ago
liked a
Space over 1 year ago
updated a
Space over 1 year ago
published a
Space over 1 year ago
reacted to burtenshaw's post with 🔥 over 1 year ago
Post
9304
The Hugging Face agents course is finally out!
👉
agents-course
This first unit of the course sets you up with all the fundamentals to become a pro in agents.
- What's an AI Agent?
- What are LLMs?
- Messages and Special Tokens
- Understanding AI Agents through the Thought-Action-Observation Cycle
- Thought, Internal Reasoning and the Re-Act Approach
- Actions, Enabling the Agent to Engage with Its Environment
- Observe, Integrating Feedback to Reflect and Adapt
👉
This first unit of the course sets you up with all the fundamentals to become a pro in agents.
- What's an AI Agent?
- What are LLMs?
- Messages and Special Tokens
- Understanding AI Agents through the Thought-Action-Observation Cycle
- Thought, Internal Reasoning and the Re-Act Approach
- Actions, Enabling the Agent to Engage with Its Environment
- Observe, Integrating Feedback to Reflect and Adapt
liked a
dataset over 1 year ago
liked a
Space over 1 year ago