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Fixings grammatical errors in Doc Files (#9647)
Fixing some typos and grammatical error is doc file. @eyurtsev , @baskaryan Thanks --------- Co-authored-by: Aayush <142384656+AayushShorthillsAI@users.noreply.github.com> Co-authored-by: Ishita Chauhan <136303787+IshitaChauhanShortHillsAI@users.noreply.github.com>
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@ -47,8 +47,8 @@ If you’re working on something you’re proud of, and think the LangChain comm
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Here’s where our team hangs out, talks shop, spotlights cool work, and shares what we’re up to. We’d love to see you there too.
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- **[Twitter](https://twitter.com/LangChainAI):** we post about what we’re working on and what cool things we’re seeing in the space. If you tag @langchainai in your post, we’ll almost certainly see it, and can snow you some love!
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- **[Discord](https://discord.gg/6adMQxSpJS):** connect with with >30k developers who are building with LangChain
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- **[Twitter](https://twitter.com/LangChainAI):** we post about what we’re working on and what cool things we’re seeing in the space. If you tag @langchainai in your post, we’ll almost certainly see it, and can show you some love!
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- **[Discord](https://discord.gg/6adMQxSpJS):** connect with >30k developers who are building with LangChain
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- **[GitHub](https://github.com/langchain-ai/langchain):** open pull requests, contribute to a discussion, and/or contribute
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- **[Subscribe to our bi-weekly Release Notes](https://6w1pwbss0py.typeform.com/to/KjZB1auB):** a twice/month email roundup of the coolest things going on in our orbit
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- **Slack:** if you’re building an application in production at your company, we’d love to get into a Slack channel together. Fill out [this form](https://airtable.com/appwQzlErAS2qiP0L/shrGtGaVBVAz7NcV2) and we’ll get in touch about setting one up.
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@ -3,7 +3,7 @@ sidebar_position: 3
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---
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# Comparison Evaluators
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Comparison evaluators in LangChain help measure two different chain or LLM outputs. These evaluators are helpful for comparative analyses, such as A/B testing between two language models, or comparing different versions of the same model. They can also be useful for things like generating preference scores for ai-assisted reinforcement learning.
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Comparison evaluators in LangChain help measure two different chains or LLM outputs. These evaluators are helpful for comparative analyses, such as A/B testing between two language models, or comparing different versions of the same model. They can also be useful for things like generating preference scores for ai-assisted reinforcement learning.
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These evaluators inherit from the `PairwiseStringEvaluator` class, providing a comparison interface for two strings - typically, the outputs from two different prompts or models, or two versions of the same model. In essence, a comparison evaluator performs an evaluation on a pair of strings and returns a dictionary containing the evaluation score and other relevant details.
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@ -16,7 +16,7 @@ Here's a summary of the key methods and properties of a comparison evaluator:
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- `requires_input`: This property indicates whether this evaluator requires an input string.
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- `requires_reference`: This property specifies whether this evaluator requires a reference label.
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Detailed information about creating custom evaluators and the available built-in comparison evaluators are provided in the following sections.
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Detailed information about creating custom evaluators and the available built-in comparison evaluators is provided in the following sections.
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import DocCardList from "@theme/DocCardList";
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