using System.Text; using LLama.Native; namespace LLama.Abstractions; /// /// The parameters for initializing a LLama context from a model. /// public interface IContextParams { /// /// Model context size (n_ctx) /// uint ContextSize { get; set; } /// /// batch size for prompt processing (must be >=32 to use BLAS) (n_batch) /// uint BatchSize { get; set; } /// /// Seed for the random number generator (seed) /// uint Seed { get; set; } /// /// Use f16 instead of f32 for memory kv (memory_f16) /// bool UseFp16Memory { get; set; } /// /// Compute perplexity over the prompt (perplexity) /// bool Perplexity { get; set; } /// /// Whether to use embedding mode. (embedding) Note that if this is set to true, /// The LLamaModel won't produce text response anymore. /// bool EmbeddingMode { get; set; } /// /// RoPE base frequency (null to fetch from the model) /// float? RopeFrequencyBase { get; set; } /// /// RoPE frequency scaling factor (null to fetch from the model) /// float? RopeFrequencyScale { get; set; } /// /// Use experimental mul_mat_q kernels /// bool MulMatQ { get; set; } /// /// The encoding to use for models /// Encoding Encoding { get; set; } /// /// Number of threads (null = autodetect) (n_threads) /// uint? Threads { get; set; } /// /// Number of threads to use for batch processing (null = autodetect) (n_threads) /// uint? BatchThreads { get; set; } /// /// YaRN extrapolation mix factor /// float? YarnExtrapolationFactor { get; set; } /// /// YaRN magnitude scaling factor /// float? YarnAttentionFactor { get; set; } /// /// YaRN low correction dim /// float? YarnBetaFast { get; set; } /// /// YaRN high correction dim /// float? YarnBetaSlow { get; set; } /// /// YaRN original context length /// uint? YarnOriginalContext { get; set; } /// /// YaRN scaling method to use. /// RopeScalingType? YarnScalingType { get; set; } }