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fix typo's

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Sofie Van Landeghem 2023-12-29 21:28:03 +01:00 committed by GitHub
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website/docs/api/large-language-models.mdx
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@ -225,7 +225,7 @@ All tasks are registered in the `llm_tasks` registry.
dataset across multiple storage units for easier processing and lookups. In
`spacy-llm` we use this term (synonymously: "mapping") to describe the splitting
up of prompts if they are too long for a model to handle, and "fusing"
(synonymously: "reducing") to describe how the model responses for several shars
(synonymously: "reducing") to describe how the model responses for several shards
are merged back together into a single document.
Prompts are broken up in a manner that _always_ keeps the prompt in the template
@ -239,10 +239,10 @@ prompt template for our fictional, sharding-supporting task looks like this:
```
Estimate the sentiment of this text:
"{text}"
Estimated entiment:
Estimated sentiment:
```
Depening on how tokens are counted exactly (this is a config setting), we might
Depending on how tokens are counted exactly (this is a config setting), we might
come up with `n = 12` tokens for the number of tokens in the prompt
instructions. Furthermore let's assume that our `text` is "This has been
amazing - I can't remember the last time I left the cinema so impressed." -
@ -259,7 +259,7 @@ _(Prompt 1/2)_
```
Estimate the sentiment of this text:
"This has been amazing - I can't remember "
Estimated entiment:
Estimated sentiment:
```
_(Prompt 2/2)_
@ -267,7 +267,7 @@ _(Prompt 2/2)_
```
Estimate the sentiment of this text:
"the last time I left the cinema so impressed."
Estimated entiment:
Estimated sentiment:
```
The reduction step is task-specific - a sentiment estimation task might e. g. do