{"action":"created","issue":{"url":"https://api.github.com/repos/google-research/bert/issues/139","repository_url":"https://api.github.com/repos/google-research/bert","labels_url":"https://api.github.com/repos/google-research/bert/issues/139/labels{/name}","comments_url":"https://api.github.com/repos/google-research/bert/issues/139/comments","events_url":"https://api.github.com/repos/google-research/bert/issues/139/events","html_url":"https://github.com/google-research/bert/issues/139","id":381885294,"node_id":"MDU6SXNzdWUzODE4ODUyOTQ=","number":139,"title":"BERT as a language model","user":{"login":"eaplatanios","id":1294940,"node_id":"MDQ6VXNlcjEyOTQ5NDA=","avatar_url":"https://avatars2.githubusercontent.com/u/1294940?v=4","gravatar_id":"","url":"https://api.github.com/users/eaplatanios","html_url":"https://github.com/eaplatanios","followers_url":"https://api.github.com/users/eaplatanios/followers","following_url":"https://api.github.com/users/eaplatanios/following{/other_user}","gists_url":"https://api.github.com/users/eaplatanios/gists{/gist_id}","starred_url":"https://api.github.com/users/eaplatanios/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/eaplatanios/subscriptions","organizations_url":"https://api.github.com/users/eaplatanios/orgs","repos_url":"https://api.github.com/users/eaplatanios/repos","events_url":"https://api.github.com/users/eaplatanios/events{/privacy}","received_events_url":"https://api.github.com/users/eaplatanios/received_events","type":"User","site_admin":false},"labels":[],"state":"closed","locked":false,"assignee":null,"assignees":[],"milestone":null,"comments":2,"created_at":"2018-11-17T17:56:27Z","updated_at":"2018-11-24T00:47:21Z","closed_at":"2018-11-23T22:01:23Z","author_association":"NONE","body":"Hi there,\r\n\r\nFirst of all, thanks for open-sourcing BERT as a concise independent codebase that's easy to go through and play around with. :)\r\n\r\nI have a question regarding just applying BERT as a language model scoring function. For example, say I have a text file containing one sentence per line. Is there a simple way to just score those sentences with their likelihood under the BERT language model?\r\n\r\nThanks,\r\nAnthony"},"comment":{"url":"https://api.github.com/repos/google-research/bert/issues/comments/441333585","html_url":"https://github.com/google-research/bert/issues/139#issuecomment-441333585","issue_url":"https://api.github.com/repos/google-research/bert/issues/139","id":441333585,"node_id":"MDEyOklzc3VlQ29tbWVudDQ0MTMzMzU4NQ==","user":{"login":"eaplatanios","id":1294940,"node_id":"MDQ6VXNlcjEyOTQ5NDA=","avatar_url":"https://avatars2.githubusercontent.com/u/1294940?v=4","gravatar_id":"","url":"https://api.github.com/users/eaplatanios","html_url":"https://github.com/eaplatanios","followers_url":"https://api.github.com/users/eaplatanios/followers","following_url":"https://api.github.com/users/eaplatanios/following{/other_user}","gists_url":"https://api.github.com/users/eaplatanios/gists{/gist_id}","starred_url":"https://api.github.com/users/eaplatanios/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/eaplatanios/subscriptions","organizations_url":"https://api.github.com/users/eaplatanios/orgs","repos_url":"https://api.github.com/users/eaplatanios/repos","events_url":"https://api.github.com/users/eaplatanios/events{/privacy}","received_events_url":"https://api.github.com/users/eaplatanios/received_events","type":"User","site_admin":false},"created_at":"2018-11-24T00:47:21Z","updated_at":"2018-11-24T00:47:21Z","author_association":"NONE","body":"Thanks! I see. I guess that makes sense in the context of the masked LM."}}
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