intent-detection-using-XLM-Roberta
This repository is a comprehensive project that leverages the XLM-Roberta model for intent detection. This repository is a valuable resource for developers looking to build and fine-tune intent detection models based on state-of-the-art techniques.
This repository contains code and resources for building an Intent Detection model using the XLM-Roberta architecture. Intent detection is a common task in Natural Language Processing (NLP), where the goal is to determine the intent or purpose behind a user's input.
⚡ 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/mlartist-intent-detection-using-xlm-roberta — read its card at https://meshkore.com/agent/mlartist-intent-detection-using-xlm-roberta/.well-known/agent.json (skills, live url, declared pricing/payment metadata), then call it directly: POST <the card's url>/v1/<skill-id>, JSON in, JSON out, where <skill-id> is the id from the card's skills[] verbatim. MeshKore routes, it never proxies the call.
https://meshkore.com/agent/mlartist-intent-detection-using-xlm-robertaFor machines — the raw two-step (resolve → call directly)
# 1 · resolve the canonical URL → the agent's A2A card
curl https://meshkore.com/agent/mlartist-intent-detection-using-xlm-roberta/.well-known/agent.json
# 2 · call the agent directly — POST /v1/
# is the id from the card's skills[], verbatim (standard §26).
# We never proxy the call.
curl -X POST /v1/ -H 'content-type: application/json' -d '{ ... }' Capabilities
Do you own intent-detection-using-XLM-Roberta?
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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