twitter-roberta-base-emotion on RBLN NPU¶
{"attn": "eager", "axes": [{"axis": "lmcache", "options": [{"label": "Off", "value": "off"}, {"label": "LMCache (CPU)", "value": "cpu"}, {"label": "LMCache (RDS)", "value": "rds"}], "title": "KV Offload"}, {"axis": "kv_connector", "options": [{"label": "Off", "value": "off"}, {"label": "LMCache (CPU)", "value": "lmcache_cpu"}, {"label": "LMCache (RDS)", "value": "lmcache_rds"}], "title": "KV Offload"}, {"axis": "prefix_caching", "options": [{"label": "On", "value": "on"}, {"label": "On (sub-block)", "value": "on_sub_block"}, {"label": "Off", "value": "off"}], "title": "Prefix Caching"}, {"axis": "spec_decode", "options": [{"label": "Off", "value": "off"}, {"label": "N-gram", "value": "ngram"}, {"label": "EAGLE-3", "value": "eagle3"}, {"label": "Suffix", "value": "suffix"}, {"label": "MTP", "value": "mtp"}], "title": "Speculative Decoding"}, {"axis": "on_device_sampler", "options": [{"label": "On", "value": "on"}, {"label": "Off", "value": "off"}], "title": "On-device Sampler"}, {"axis": "structured_output", "options": [{"label": "On", "value": "on"}, {"label": "Off", "value": "off"}], "title": "Structured Output"}], "badges": ["Classification", "512 ctx", {"hl": true, "text": "vllm-rbln"}, "eager", "Text"], "client": "curl http://localhost:8000/classify \\\n -H \"Content-Type: application/json\" \\\n -d \u0027{\n \"model\": \"twitter-roberta-base-emotion\",\n \"input\": \"I am so happy with this!\"\n }\u0027", "features": {"api": true, "mm": false, "text": true}, "hf": "https://huggingface.co/cardiffnlp/twitter-roberta-base-emotion", "installLine": "pip install rebel-compiler vllm-rbln", "model": "cardiffnlp/twitter-roberta-base-emotion", "name": "twitter-roberta-base-emotion", "provider": "cardiffnlp", "strategies": [{"label": "RSD", "nodes": null, "options": [{"attn": null, "features": {}, "label": null, "modelImpl": "transformers", "note": null, "npus": 1, "roles": [{"cmd": "vllm serve cardiffnlp/twitter-roberta-base-emotion \\\n --max-model-len 512 \\\n --model-impl transformers \\\n --rbln-num-devices-per-local-rank 1 \\\n --served-model-name twitter-roberta-base-emotion", "role": "main"}], "skus": ["RBLN-CA22", "RBLN-CA25"], "target": null, "verified": "2026-10-16"}], "slug": "rsd", "tag": "Aggregated", "variant": "BF16"}], "text": {"en": {"strategyNote": "Served through vLLM\u0027s \u003ccode\u003e/classify\u003c/code\u003e endpoint. See \u003cstrong\u003eConfiguration\u003c/strong\u003e in the guide for the engine arguments.", "sub": "twitter-roberta-base-emotion \u2014 sequence classification model served on RBLN NPUs with RBLN vLLM over the OpenAI-compatible API.", "tag": "The vllm serve command compiles the model on first run and starts an OpenAI-compatible server."}, "ko": {"strategyNote": "vLLM\uc758 \u003ccode\u003e/classify\u003c/code\u003e \uc5d4\ub4dc\ud3ec\uc778\ud2b8\ub85c \uc11c\ube59\ub429\ub2c8\ub2e4. \uc5d4\uc9c4 \uc778\uc790\ub294 \uac00\uc774\ub4dc\uc758 \u003cstrong\u003eConfiguration\u003c/strong\u003e\uc5d0\uc11c \ud655\uc778\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.", "sub": "twitter-roberta-base-emotion \u2014 \uc2dc\ud000\uc2a4 \ubd84\ub958 \ubaa8\ub378, RBLN vLLM\uc73c\ub85c RBLN NPU\uc5d0\uc11c OpenAI \ud638\ud658 API\ub85c \uc11c\ube59\ud569\ub2c8\ub2e4.", "tag": "vllm serve \uba85\ub839\uc740 \ucd5c\ucd08 \uc2e4\ud589 \uc2dc \ubaa8\ub378\uc744 \ucef4\ud30c\uc77c\ud558\uace0 OpenAI \ud638\ud658 \uc11c\ubc84\ub97c \uc2dc\uc791\ud569\ub2c8\ub2e4."}}, "variant": "BF16"} Install the RBLN Driver on the host. An RBLN Portal account is required to install the RBLN Compiler (rebel-compiler). See the installation matrix for compatible package versions.
Guide — overview and configuration
Overview¶
cardiffnlp/twitter-roberta-base-emotion is a sequence classification model. On RBLN NPUs, the RBLN vLLM plugin compiles it on first run, then serves it through vLLM's /classify endpoint.
Configuration¶
--rbln-num-devices-per-local-rank sets how many NPU devices one engine process uses, and the RBLN Compiler partitions the model for those devices with Rebellions Scalable Design (RSD). See Model Parallelism for how RSD applies on each NPU. Changing these settings recompiles the model on the next start. Compile Cache lists every setting that does.
See the Configuration Guide for all engine arguments.
Notes and limitations¶
- The compiled artifact is cached on first run; changing the NPU count or engine arguments recompiles on the next start.