Table of Contents

Class RequestOptions

Namespace
OllamaSharp.Models
Assembly
OllamaSharp.dll

The configuration information used for a chat completions request.

public class RequestOptions
Inheritance
RequestOptions
Inherited Members

Properties

F16kv

Enable f16 key/value. (Default: False)

[JsonPropertyName("f16_kv")]
[JsonIgnore(Condition = JsonIgnoreCondition.WhenWritingNull)]
public bool? F16kv { get; set; }

Property Value

bool?

FrequencyPenalty

The penalty to apply to tokens based on their frequency in the prompt. (Default: 0.0)

[JsonPropertyName("frequency_penalty")]
[JsonIgnore(Condition = JsonIgnoreCondition.WhenWritingNull)]
public float? FrequencyPenalty { get; set; }

Property Value

float?

LogitsAll

Return logits for all the tokens, not just the last one. (Default: False)

[JsonPropertyName("logits_all")]
[JsonIgnore(Condition = JsonIgnoreCondition.WhenWritingNull)]
public bool? LogitsAll { get; set; }

Property Value

bool?

LowVram

Enable low VRAM mode. (Default: False)

[JsonPropertyName("low_vram")]
[JsonIgnore(Condition = JsonIgnoreCondition.WhenWritingNull)]
public bool? LowVram { get; set; }

Property Value

bool?

MainGpu

This option controls which GPU is used for small tensors. The overhead of splitting the computation across all GPUs is not worthwhile. The GPU will use slightly more VRAM to store a scratch buffer for temporary results. By default, GPU 0 is used.

[JsonPropertyName("main_gpu")]
[JsonIgnore(Condition = JsonIgnoreCondition.WhenWritingNull)]
public int? MainGpu { get; set; }

Property Value

int?

MinP

Alternative to the top_p, and aims to ensure a balance of quality and variety.min_p represents the minimum probability for a token to be considered, relative to the probability of the most likely token.For example, with min_p=0.05 and the most likely token having a probability of 0.9, logits with a value less than 0.05*0.9=0.045 are filtered out. (Default: 0.0)

[JsonPropertyName("min_p")]
[JsonIgnore(Condition = JsonIgnoreCondition.WhenWritingNull)]
public float? MinP { get; set; }

Property Value

float?

MiroStat

Enable Mirostat sampling for controlling perplexity. (default: 0, 0 = disabled, 1 = Mirostat, 2 = Mirostat 2.0)

[JsonPropertyName("mirostat")]
[JsonIgnore(Condition = JsonIgnoreCondition.WhenWritingNull)]
public int? MiroStat { get; set; }

Property Value

int?

MiroStatEta

Influences how quickly the algorithm responds to feedback from the generated text. A lower learning rate will result in slower adjustments, while a higher learning rate will make the algorithm more responsive. (Default: 0.1)

[JsonPropertyName("mirostat_eta")]
[JsonIgnore(Condition = JsonIgnoreCondition.WhenWritingNull)]
public float? MiroStatEta { get; set; }

Property Value

float?

MiroStatTau

Controls the balance between coherence and diversity of the output. A lower value will result in more focused and coherent text. (Default: 5.0)

[JsonPropertyName("mirostat_tau")]
[JsonIgnore(Condition = JsonIgnoreCondition.WhenWritingNull)]
public float? MiroStatTau { get; set; }

Property Value

float?

NumBatch

Prompt processing maximum batch size. (Default: 512)

[JsonPropertyName("num_batch")]
[JsonIgnore(Condition = JsonIgnoreCondition.WhenWritingNull)]
public int? NumBatch { get; set; }

Property Value

int?

NumCtx

Sets the size of the context window used to generate the next token. (Default: 2048)

[JsonPropertyName("num_ctx")]
[JsonIgnore(Condition = JsonIgnoreCondition.WhenWritingNull)]
public int? NumCtx { get; set; }

Property Value

int?

NumGpu

The number of layers to send to the GPU(s). On macOS it defaults to 1 to enable metal support, 0 to disable.

[JsonPropertyName("num_gpu")]
[JsonIgnore(Condition = JsonIgnoreCondition.WhenWritingNull)]
public int? NumGpu { get; set; }

Property Value

int?

NumGqa

The number of GQA groups in the transformer layer. Required for some models, for example it is 8 for llama2:70b

[JsonPropertyName("num_gqa")]
[JsonIgnore(Condition = JsonIgnoreCondition.WhenWritingNull)]
public int? NumGqa { get; set; }

Property Value

int?

NumKeep

Number of tokens to keep from the initial prompt. (Default: 4, -1 = all)

[JsonPropertyName("num_keep")]
[JsonIgnore(Condition = JsonIgnoreCondition.WhenWritingNull)]
public int? NumKeep { get; set; }

Property Value

int?

NumPredict

Maximum number of tokens to predict when generating text. (Default: 128, -1 = infinite generation, -2 = fill context)

[JsonPropertyName("num_predict")]
[JsonIgnore(Condition = JsonIgnoreCondition.WhenWritingNull)]
public int? NumPredict { get; set; }

Property Value

int?

NumThread

Sets the number of threads to use during computation. By default, Ollama will detect this for optimal performance. It is recommended to set this value to the number of physical CPU cores your system has (as opposed to the logical number of cores).

[JsonPropertyName("num_thread")]
[JsonIgnore(Condition = JsonIgnoreCondition.WhenWritingNull)]
public int? NumThread { get; set; }

Property Value

int?

Numa

Enable NUMA support. (Default: False)

[JsonPropertyName("numa")]
[JsonIgnore(Condition = JsonIgnoreCondition.WhenWritingNull)]
public bool? Numa { get; set; }

Property Value

bool?

PenalizeNewline

Penalize newline tokens (Default: True)

[JsonPropertyName("penalize_newline")]
[JsonIgnore(Condition = JsonIgnoreCondition.WhenWritingNull)]
public bool? PenalizeNewline { get; set; }

Property Value

bool?

PresencePenalty

The penalty to apply to tokens based on their presence in the prompt. (Default: 0.0)

[JsonPropertyName("presence_penalty")]
[JsonIgnore(Condition = JsonIgnoreCondition.WhenWritingNull)]
public float? PresencePenalty { get; set; }

Property Value

float?

RepeatLastN

Sets how far back for the model to look back to prevent repetition. (Default: 64, 0 = disabled, -1 = num_ctx)

[JsonPropertyName("repeat_last_n")]
[JsonIgnore(Condition = JsonIgnoreCondition.WhenWritingNull)]
public int? RepeatLastN { get; set; }

Property Value

int?

RepeatPenalty

Sets how strongly to penalize repetitions. A higher value (e.g., 1.5) will penalize repetitions more strongly, while a lower value (e.g., 0.9) will be more lenient. (Default: 1.1)

[JsonPropertyName("repeat_penalty")]
[JsonIgnore(Condition = JsonIgnoreCondition.WhenWritingNull)]
public float? RepeatPenalty { get; set; }

Property Value

float?

Seed

Sets the random number seed to use for generation. Setting this to a specific number will make the model generate the same text for the same prompt. (Default: 0)

[JsonPropertyName("seed")]
[JsonIgnore(Condition = JsonIgnoreCondition.WhenWritingNull)]
public int? Seed { get; set; }

Property Value

int?

Stop

Sets the stop sequences to use. When this pattern is encountered the LLM will stop generating text and return. Multiple stop patterns may be set by specifying multiple separate stop parameters in a modelfile.

[JsonPropertyName("stop")]
[JsonIgnore(Condition = JsonIgnoreCondition.WhenWritingNull)]
public string[]? Stop { get; set; }

Property Value

string[]

Temperature

The temperature of the model. Increasing the temperature will make the model answer more creatively. (Default: 0.8)

[JsonPropertyName("temperature")]
[JsonIgnore(Condition = JsonIgnoreCondition.WhenWritingNull)]
public float? Temperature { get; set; }

Property Value

float?

TfsZ

Tail free sampling is used to reduce the impact of less probable tokens from the output. A higher value (e.g., 2.0) will reduce the impact more, while a value of 1.0 disables this setting. (default: 1)

[JsonPropertyName("tfs_z")]
[JsonIgnore(Condition = JsonIgnoreCondition.WhenWritingNull)]
public float? TfsZ { get; set; }

Property Value

float?

TopK

Reduces the probability of generating nonsense. A higher value (e.g. 100) will give more diverse answers, while a lower value (e.g. 10) will be more conservative. (Default: 40)

[JsonPropertyName("top_k")]
[JsonIgnore(Condition = JsonIgnoreCondition.WhenWritingNull)]
public int? TopK { get; set; }

Property Value

int?

TopP

Works together with top-k. A higher value (e.g., 0.95) will lead to more diverse text, while a lower value (e.g., 0.5) will generate more focused and conservative text. (Default: 0.9)

[JsonPropertyName("top_p")]
[JsonIgnore(Condition = JsonIgnoreCondition.WhenWritingNull)]
public float? TopP { get; set; }

Property Value

float?

TypicalP

The typical-p value to use for sampling. Locally Typical Sampling implementation described in the paper https://arxiv.org/abs/2202.00666. (Default: 1.0)

[JsonPropertyName("typical_p")]
[JsonIgnore(Condition = JsonIgnoreCondition.WhenWritingNull)]
public float? TypicalP { get; set; }

Property Value

float?

UseMlock

Lock the model in memory to prevent swapping. This can improve performance, but it uses more RAM and may slow down loading. (Default: False)

[JsonPropertyName("use_mlock")]
[JsonIgnore(Condition = JsonIgnoreCondition.WhenWritingNull)]
public bool? UseMlock { get; set; }

Property Value

bool?

UseMmap

Models are mapped into memory by default, which allows the system to load only the necessary parts as needed. Disabling mmap makes loading slower but reduces pageouts if you're not using mlock. If the model is bigger than your RAM, turning off mmap stops it from loading. (Default: True)

[JsonPropertyName("use_mmap")]
[JsonIgnore(Condition = JsonIgnoreCondition.WhenWritingNull)]
public bool? UseMmap { get; set; }

Property Value

bool?

VocabOnly

Load only the vocabulary, not the weights. (Default: False)

[JsonPropertyName("vocab_only")]
[JsonIgnore(Condition = JsonIgnoreCondition.WhenWritingNull)]
public bool? VocabOnly { get; set; }

Property Value

bool?
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