How to filter some fo the personalized data?
Open
Nobody has claimed this yet.
- Dominant language
- Python
- Stars
- 12.3k
- Forks
- 1.1k
- PR merge metrics
- No merged PRs in 30d
Description
First, thank you for open souring the data.
Like id=3 in zh_helpfulness or id=6 in zh_honesty, it has something like "我的创造者是复旦大学自然语言处理实验室和上海人工智能实验室". This is not good for training our own model. Is there a way to filter out these data other than guessing some random keywords?
Contributor guide
No contributing guide indexed for this repository
First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
The issue does not name a file, test, or entry point to inspect. First clarify whether the project should provide a filtering mechanism or document an existing one, and define which personalized records must be excluded; completion cannot be assessed until that scope and an acceptance check are specified.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python
- Domain
- data, machine-learning
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 25/100