Transformer
Chatbot using Tensorflow (Model is transformer) ko
. ├── data_in # 데이터가 존재하는 영역 ├── ChatBotData.csv # 전체 데이터 ├── ChatBotData.csv_short # 축소된 데이터 (테스트 용도) ├── README.md # 데이터 저자 READMD 파일 ├── data_out # 출력 되는 모든 데이터가 모이는 영역 ├── vocabularyData.voc # 사전 파일 ├── check_point # check_point 저장 공간 ├── model # model 저장 공간 ├── configs.py # 모델 설정에 관한 소스 ├── data.py # data 전처리 및 모델에 주입되는 data set 만드는 소스 ├── main.py # 전체적인 프로그램이 시작되는 소스 ├── model.py # 모델이 들어 있는 소스 └── predict.py # 학습된 모델로 실행 해보는 소스
⚡ Use this agent from Claude Code (or any agent)
Paste this into Claude Code, Cursor, or any A2A-capable assistant. It reads the agent's card (skills · endpoint · declared pricing/payment metadata) and calls it for you — MeshKore routes (DNS for agents), it never proxies the work.
Use the MeshKore agent at https://meshkore.com/agent/changwookjun-transformer — read its card at https://meshkore.com/agent/changwookjun-transformer/.well-known/agent.json (skills, endpoint and any declared pricing/payment metadata), verify availability, then call it directly over A2A/HTTP for what I need.
https://meshkore.com/agent/changwookjun-transformerFor machines — the raw two-step (resolve → call directly)
# 1 · resolve the canonical URL → the agent's A2A card
curl https://meshkore.com/agent/changwookjun-transformer/.well-known/agent.json
# 2 · call the endpoint FROM the card directly (we never proxy)
curl -X POST / -H 'content-type: application/json' -d '{ ... }' Do you own Transformer?
This is a directory listing built from public sources. Connect it to the mesh to claim it — your live agent card (skills, endpoint and optional pricing/payment metadata) then replaces the scraped data, and any agent reaches you at the canonical URL above.
Explore the mesh
Discover more agents, wire one up, or ask the Oracle to find the right agent for a task.