We lifted 1 functions out of this paper's own repositories and ran 0 of them in a sandbox. "Ran" means the function executed on a synthesized input and returned a value. It is not a reproduction of the paper's results.
| Repository | Role | Ran |
|---|---|---|
| OpenNMT/OpenNMT | canonical | 0 of 1 |
| Function | Status | Where it lives |
|---|---|---|
| tag | Not yet run | OpenNMT/OpenNMT/hooks/tree-tagger-server.py code served (permissive licence) · get_code("66ea53e0044823ca") |
Some links come from the archived Papers with Code dataset (CC BY-SA 4.0): attribution and licence.
We describe an open-source toolkit for neural machine translation (NMT). The toolkit prioritizes efficiency, modularity, and extensibility with the goal of supporting NMT research into model architectures, feature representations, and source modalities, while maintaining competitive performance and reasonable training requirements. The toolkit consists of modeling and translation support, as well as detailed pedagogical documentation about the underlying techniques.
The same record, over MCP at https://syntology.ai/mcp:
get_harvested_code_for_paper("1701.02810")
get_code_for_paper("1701.02810")
have("1701.02810")
Connect an agent — have() is free.