Comments (1)
Thank you for your question.
- The
demos
data consists of demonstrations (in-context learning) for the Atomic Fact Generator. So it's part of the data the model uses, rather than being used as the test data. Annotations in the demos data are written by humans. - We are validating each atomic fact based on the Wikipedia article about the subject. Thus, retrieval is restricted to this single article. Please refer to the Implementation details in 4.1.2 of the paper. It is possible to relax this restriction but we empirically found this to be working better.
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Related Issues (20)
- Having issues on using LLAMA-7B model HOT 2
- Scoring existing generated text HOT 1
- Typo here HOT 1
- FileNotFoundError (demons.json) for custom knowledge base HOT 2
- Regarding human evaluation HOT 2
- The chatgpt-based AtomicFactGenerator of FactScore sometimes abstain from answering HOT 4
- Generation details for models under data/labeled HOT 1
- How to modify the code to calculate factscore between any two paragraphs/sentences without retrieval steps? HOT 1
- Issue running get_score() on M1 Mac due to Torch build HOT 1
- Any way to run without an OpenAI key? HOT 3
- Some cases couldn't be found in the default db HOT 2
- problem using the factscorer function with LLaMa HOT 1
- AssertionError: `topic` in your data (Jessie Mae Brown Beavers) is likely to be not a valid title in the DB. HOT 1
- Move to ChatCompletion endpoint for call_GPT3
- InvalidRequestError: The model `text-davinci-003` has been deprecated HOT 2
- sqlite3.DatabaseError: file is not a database error after Installation
- About the enwiki-20230401 HOT 5
- Batching for speed.
- Improved version for speed and openai updates
- Maintaining core factscore in a new repository
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from factscore.