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(docs) add logprobs, top_logprobs

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ishaan-jaff
2023-12-26 14:53:30 +05:30
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docs/my-website/docs/completion/input.md
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@@ -120,7 +120,7 @@ def completion(
## Optional Fields
`temperature`: *number or null (optional)* - The sampling temperature to be used, between 0 and 2. Higher values like 0.8 produce more random outputs, while lower values like 0.2 make outputs more focused and deterministic.
- `temperature`: *number or null (optional)* - The sampling temperature to be used, between 0 and 2. Higher values like 0.8 produce more random outputs, while lower values like 0.2 make outputs more focused and deterministic.
- `top_p`: *number or null (optional)* - An alternative to sampling with temperature. It instructs the model to consider the results of the tokens with top_p probability. For example, 0.1 means only the tokens comprising the top 10% probability mass are considered.
@@ -160,6 +160,10 @@ def completion(
- `timeout`: *int (optional)* - Timeout in seconds for completion requests (Defaults to 600 seconds)
- `logprobs`: * bool (optional)* - Whether to return log probabilities of the output tokens or not. If true returns the log probabilities of each output token returned in the content of message
- `top_logprobs`: *int (optional)* - An integer between 0 and 5 specifying the number of most likely tokens to return at each token position, each with an associated log probability. `logprobs` must be set to true if this parameter is used.
#### Deprecated Params
- `functions`: *array* - A list of functions that the model may use to generate JSON inputs. Each function should have the following properties: