Cohere Command R (08-2024)

To change the model responses, you can change the values of the following parameters in the playground or the API.

Maximum output tokens

The maximum number of tokens that you want the model to generate for each response. Estimate four characters per token. Because you're prompting a chat model, the response depends on the prompt and each response doesn't necessarily use up the maximum allocated tokens.

Preamble override

An initial context or guiding message for a chat model. When you don't give a preamble to a chat model, the default preamble for that model is used. You can assign a preamble in the Preamble override parameter, for the models. The default preamble for the Cohere family is:

You are Command.
            You are an extremely capable large language model built by Cohere. 
            You are given instructions programmatically via an API
            that you follow to the best of your ability.

Overriding the default preamble is optional. When specified, the preamble override replaces the default Cohere preamble. When adding a preamble, for best results, give the model context, instructions, and a conversation style.

Tip

For chat models without the preamble override parameter, you can include a preamble in the chat conversation and directly ask the model to answer in a certain way.

Safety Mode

Adds a safety instruction for the model to use when generating responses. Options are:

• Contextual: (Default) Puts fewer constraints on the output. It maintains core protections by aiming to reject harmful or illegal suggestions, but it allows profanity and some toxic content, sexually explicit and violent content, and content that contains medical, financial, or legal information. Contextual mode is suited for entertainment, creative, or academic use.
• Strict: Aims to avoid sensitive topics, such as violent or sexual acts and profanity. This mode aims to provide a safer experience by prohibiting responses or recommendations that it finds inappropriate. Strict mode is suited for corporate use, such as for corporate communications and customer service.
• Off: No safety mode is applied.

Temperature

The level of randomness used to generate the output text.

Tip

Start with the temperature set to 0 or less than one, and increase the temperature as you regenerate the prompts for a more creative output. High temperatures can introduce hallucinations and factually incorrect information.

Top p

A sampling method that controls the cumulative probability of the top tokens to consider for the next token. Assign p a decimal number between 0 and 1 for the probability. For example, enter 0.75 for the top 75 percent to be considered. Set p to 1 to consider all tokens.

Top k

A sampling method in which the model chooses the next token randomly from the top k most likely tokens. A high value for k generates more random output, which makes the output text sound more natural. The default value for k is 0 for Cohere Command models and -1 for Meta Llama models, which means that the model should consider all tokens and not use this method.

Frequency penalty

A penalty that's assigned to a token when that token appears frequently. High penalties encourage fewer repeated tokens and produce a more random output.

For the Meta Llama family models, this penalty can be positive or negative. Positive numbers encourage the model to use new tokens and negative numbers encourage the model to repeat the tokens. Set to 0 to disable.

Presence penalty

A penalty that's assigned to each token when it appears in the output to encourage generating outputs with tokens that haven't been used.

Seed

A parameter that makes a best effort to sample tokens deterministically. When this parameter is assigned a value, the large language model aims to return the same result for repeated requests when you assign the same seed and parameters for the requests.

Allowed values are integers and assigning a large or a small seed value doesn't affect the result. Assigning a number for the seed parameter is similar to tagging the request with a number. The large language model aims to generate the same set of tokens for the same integer in consecutive requests. This feature is especially useful for debugging and testing. The seed parameter has no maximum value for the API, and in the Console, its maximum value is 9999. Leaving the seed value blank in the Console, or null in the API disables this feature.

Warning

The seed parameter might not produce the same result in the long-run, because the model updates in the OCI Generative AI service might invalidate the seed.