{"schema_version":"onlylabs.public_signal.v1","title":"AI21 Labs Repo: AI21Labs/sense-bert","description":"AI21 Labs repo signal with public source context, captured evidence pages, related signals, and category-scoped analysis context.","url":"https://onlylabs.fyi/signals/74700193-da5c-4b6d-92d8-781a0b8941fc","json_url":"https://onlylabs.fyi/signals/74700193-da5c-4b6d-92d8-781a0b8941fc/signal.json","generated_at":"2026-06-11T04:20:02.323328+00:00","org":{"slug":"ai21","name":"AI21 Labs","category":"neolab","category_label":"Neolab","dossier_url":"https://onlylabs.fyi/labs/ai21","dossier_json_url":"https://onlylabs.fyi/labs/ai21/dossier.json"},"related_urls":{"signal":"https://onlylabs.fyi/signals/74700193-da5c-4b6d-92d8-781a0b8941fc","signal_json":"https://onlylabs.fyi/signals/74700193-da5c-4b6d-92d8-781a0b8941fc/signal.json","source":"https://github.com/AI21Labs/sense-bert","lab_dossier":"https://onlylabs.fyi/labs/ai21","lab_dossier_json":"https://onlylabs.fyi/labs/ai21/dossier.json","analysis":"https://onlylabs.fyi/analysis/ai21","analysis_json":"https://onlylabs.fyi/analysis/ai21/analysis.json","analysis_evidence_json":"https://onlylabs.fyi/analysis/ai21/evidence.json","category":"https://onlylabs.fyi/neolabs","category_json":"https://onlylabs.fyi/neolabs.json","category_feed":"https://onlylabs.fyi/neolabs/feed.xml","category_signals_json":"https://onlylabs.fyi/signals.json?category=neolab","topic":null,"topic_signals_json":null,"topic_feed":null,"data_business":null},"answer_pack":{"answer":"AI21 Labs published AI21Labs/sense-bert (Python). 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Language: Python License: Apache-2.0 Stars: 48 Forks: 11 Open issues: 5 Created: 2020-07-06T07:54:34Z Pushed: 2023-03-24T23:47:37Z Default branch: master Fork: no Archived: yes README: SenseBERT: Driving Some Sense into BERT This is the code for loading the SenseBERT model, described in [our paper](https://www.aclweb.org/anthology/2020.acl-main.423.pdf) from ACL 2020. Available models We made two SenseBERT models public: * sensebert-base-uncased * sensebert-large-uncased These models have the same number of parameters as Google's BERT models, except for the following (both changes are described in our paper thoroughly): 1. We use a larger vocabulary. 2. We add a supersense prediction head. The sense embeddings are also used as inputs to the model. Requirements * Python 3.7 or higher * TensorFlow 1.15 * NLTK You can install these using: ```bash pip install -r requirements.txt ``` Usage Supersense and MLM predictions This is an example for making Masked Language Modeling (MLM) and supersense predictions based on SenseBERT: ```python import tensorflow as tf from..."},"evidence_pages":[{"url":"https://github.com/AI21Labs/sense-bert","final_url":"https://github.com/AI21Labs/sense-bert","title":"AI21Labs/sense-bert repository metadata","http_status":200,"content_type":"application/json","capture_method":"plain","fetched_at":"2026-06-11T04:20:02.323328+00:00","bytes":11453,"raw_path":"74c7bc08fe28c07c161398c7d0d84bb23182c81ee5cb67ff3092f750327140df.json","content_hash":"3e09e0a317e619bdcb649cce8186949c6dea8cfd940ced9a622b307c45c06876","excerpt_chars":1200,"truncated":true,"excerpt":"AI21Labs/sense-bert Description: This is the code for loading the SenseBERT model, described in our paper from ACL 2020. Language: Python License: Apache-2.0 Stars: 48 Forks: 11 Open issues: 5 Created: 2020-07-06T07:54:34Z Pushed: 2023-03-24T23:47:37Z Default branch: master Fork: no Archived: yes README: SenseBERT: Driving Some Sense into BERT This is the code for loading the SenseBERT model, described in [our paper](https://www.aclweb.org/anthology/2020.acl-main.423.pdf) from ACL 2020. Available models We made two SenseBERT models public: * sensebert-base-uncased * sensebert-large-uncased These models have the same number of parameters as Google's BERT models, except for the following (both changes are described in our paper thoroughly): 1. We use a larger vocabulary. 2. We add a supersense prediction head. The sense embeddings are also used as inputs to the model. 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