Model.md

google.generativeai.protos.Model

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Information about a Generative Language Model.

Attributes
name	str Required. The resource name of the Model. Refer to Model variants <https://ai.google.dev/gemini-api/docs/models/gemini#model-variations>__ for all allowed values. Format: models/{model} with a {model} naming convention of: "{base_model_id}-{version}" Examples: models/gemini-1.5-flash-001
base_model_id	str Required. The name of the base model, pass this to the generation request. Examples: gemini-1.5-flash
version	str Required. The version number of the model. This represents the major version (1.0 or 1.5)
display_name	str The human-readable name of the model. E.g. "Gemini 1.5 Flash". The name can be up to 128 characters long and can consist of any UTF-8 characters.
description	str A short description of the model.
input_token_limit	int Maximum number of input tokens allowed for this model.
output_token_limit	int Maximum number of output tokens available for this model.
supported_generation_methods	MutableSequence[str] The model's supported generation methods. The corresponding API method names are defined as Pascal case strings, such as generateMessage and generateContent.
temperature	float Controls the randomness of the output. Values can range over [0.0,max_temperature], inclusive. A higher value will produce responses that are more varied, while a value closer to 0.0 will typically result in less surprising responses from the model. This value specifies default to be used by the backend while making the call to the model.
max_temperature	float The maximum temperature this model can use.
top_p	float For Nucleus sampling <https://ai.google.dev/gemini-api/docs/prompting-strategies#top-p>__. Nucleus sampling considers the smallest set of tokens whose probability sum is at least top_p. This value specifies default to be used by the backend while making the call to the model.
top_k	int For Top-k sampling. Top-k sampling considers the set of top_k most probable tokens. This value specifies default to be used by the backend while making the call to the model. If empty, indicates the model doesn't use top-k sampling, and top_k isn't allowed as a generation parameter.