Parallel-Seq2Seq
A new seq2seq model for fast training.
PS2S is a new seq2seq model for fast training. I proposed this model in July 2017 in the context of the Seq2seq-Chatbot-for-Keras project, in case of publication using PS2S, please cite paper [[1]]( As this model was successfully applied to generative chatbots, I’m now providing a general purpose TensorFlow-based PS2S toolbox, and to give you a taste of its performance, I’ve also provided a didactic toy example in which the user can train a PS2S-based neural translator in just 15 minutes of CPU processing (just run toy_example_neural_translation.py).
⚡ 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/oswaldoludwig-parallel-seq2seq — read its card at https://meshkore.com/agent/oswaldoludwig-parallel-seq2seq/.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/oswaldoludwig-parallel-seq2seqFor machines — the raw two-step (resolve → call directly)
# 1 · resolve the canonical URL → the agent's A2A card
curl https://meshkore.com/agent/oswaldoludwig-parallel-seq2seq/.well-known/agent.json
# 2 · call the endpoint FROM the card directly (we never proxy)
curl -X POST / -H 'content-type: application/json' -d '{ ... }' Capabilities
Do you own Parallel-Seq2Seq?
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.
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