mistralrs

Enum ModelSelected

Source 
pub enum ModelSelected {

Show 15 variants    Toml {
        file: String,
    },
    Run {
Show 17 fields
        model_id: String,
        tokenizer_json: Option<String>,
        dtype: ModelDType,
        topology: Option<String>,
        organization: Option<IsqOrganization>,
        write_uqff: Option<PathBuf>,
        from_uqff: Option<String>,
        imatrix: Option<PathBuf>,
        calibration_file: Option<PathBuf>,
        max_edge: Option<u32>,
        max_seq_len: usize,
        max_batch_size: usize,
        max_num_images: Option<usize>,
        max_image_length: Option<usize>,
        hf_cache_path: Option<PathBuf>,
        matformer_config_path: Option<PathBuf>,
        matformer_slice_name: Option<String>,
    
},
    Plain {
Show 15 fields
        model_id: String,
        tokenizer_json: Option<String>,
        arch: Option<NormalLoaderType>,
        dtype: ModelDType,
        topology: Option<String>,
        organization: Option<IsqOrganization>,
        write_uqff: Option<PathBuf>,
        from_uqff: Option<String>,
        imatrix: Option<PathBuf>,
        calibration_file: Option<PathBuf>,
        max_seq_len: usize,
        max_batch_size: usize,
        hf_cache_path: Option<PathBuf>,
        matformer_config_path: Option<PathBuf>,
        matformer_slice_name: Option<String>,
    
},
    XLora {
Show 13 fields
        model_id: Option<String>,
        tokenizer_json: Option<String>,
        xlora_model_id: String,
        order: String,
        tgt_non_granular_index: Option<usize>,
        arch: Option<NormalLoaderType>,
        dtype: ModelDType,
        topology: Option<String>,
        write_uqff: Option<PathBuf>,
        from_uqff: Option<String>,
        max_seq_len: usize,
        max_batch_size: usize,
        hf_cache_path: Option<PathBuf>,
    
},
    Lora {
        model_id: Option<String>,
        tokenizer_json: Option<String>,
        adapter_model_id: String,
        arch: Option<NormalLoaderType>,
        dtype: ModelDType,
        topology: Option<String>,
        write_uqff: Option<PathBuf>,
        from_uqff: Option<String>,
        max_seq_len: usize,
        max_batch_size: usize,
        hf_cache_path: Option<PathBuf>,
    },
    GGUF {
        tok_model_id: Option<String>,
        quantized_model_id: String,
        quantized_filename: String,
        dtype: ModelDType,
        topology: Option<String>,
        max_seq_len: usize,
        max_batch_size: usize,
    },
    XLoraGGUF {
        tok_model_id: Option<String>,
        quantized_model_id: String,
        quantized_filename: String,
        xlora_model_id: String,
        order: String,
        tgt_non_granular_index: Option<usize>,
        dtype: ModelDType,
        topology: Option<String>,
        max_seq_len: usize,
        max_batch_size: usize,
    },
    LoraGGUF {
        tok_model_id: Option<String>,
        quantized_model_id: String,
        quantized_filename: String,
        adapters_model_id: String,
        order: String,
        dtype: ModelDType,
        topology: Option<String>,
        max_seq_len: usize,
        max_batch_size: usize,
    },
    GGML {
        tok_model_id: String,
        tokenizer_json: Option<String>,
        quantized_model_id: String,
        quantized_filename: String,
        gqa: usize,
        dtype: ModelDType,
        topology: Option<String>,
        max_seq_len: usize,
        max_batch_size: usize,
    },
    XLoraGGML {
        tok_model_id: Option<String>,
        tokenizer_json: Option<String>,
        quantized_model_id: String,
        quantized_filename: String,
        xlora_model_id: String,
        order: String,
        tgt_non_granular_index: Option<usize>,
        gqa: usize,
        dtype: ModelDType,
        topology: Option<String>,
        max_seq_len: usize,
        max_batch_size: usize,
    },
    LoraGGML {
        tok_model_id: Option<String>,
        tokenizer_json: Option<String>,
        quantized_model_id: String,
        quantized_filename: String,
        adapters_model_id: String,
        order: String,
        gqa: usize,
        dtype: ModelDType,
        topology: Option<String>,
        max_seq_len: usize,
        max_batch_size: usize,
    },
    VisionPlain {
Show 17 fields
        model_id: String,
        tokenizer_json: Option<String>,
        arch: Option<VisionLoaderType>,
        dtype: ModelDType,
        topology: Option<String>,
        write_uqff: Option<PathBuf>,
        from_uqff: Option<String>,
        max_edge: Option<u32>,
        calibration_file: Option<PathBuf>,
        imatrix: Option<PathBuf>,
        max_seq_len: usize,
        max_batch_size: usize,
        max_num_images: usize,
        max_image_length: usize,
        hf_cache_path: Option<PathBuf>,
        matformer_config_path: Option<PathBuf>,
        matformer_slice_name: Option<String>,
    
},
    DiffusionPlain {
        model_id: String,
        arch: DiffusionLoaderType,
        dtype: ModelDType,
    },
    Speech {
        model_id: String,
        dac_model_id: Option<String>,
        arch: SpeechLoaderType,
        dtype: ModelDType,
    },
    MultiModel {
        config: String,
        default_model_id: Option<String>,
    },

}

Variants§

§

Toml

Select the model from a toml file

Fields

§file: String

.toml file containing the selector configuration.

§

Run

Select a model for running via auto loader

Fields

§model_id: String

Model ID to load from. May be a HF hub repo or a local path.

§tokenizer_json: Option<String>

Path to local tokenizer.json file. If specified, it is used over any remote file.

§dtype: ModelDType

Model data type. Defaults to auto.

§topology: Option<String>

Path to a topology YAML file.

§organization: Option<IsqOrganization>

ISQ organization: default or moqe.

§write_uqff: Option<PathBuf>

UQFF path to write to.

§from_uqff: Option<String>

UQFF path to load from. If provided, this takes precedence over applying ISQ. Specify multiple files using a semicolon delimiter (;).

§imatrix: Option<PathBuf>

.imatrix file to enhance GGUF quantizations with.

§calibration_file: Option<PathBuf>

Generate and utilize an imatrix to enhance GGUF quantizations.

§max_edge: Option<u32>

Automatically resize and pad images to this maximum edge length. Aspect ratio is preserved. Only supported on specific vision models.

§max_seq_len: usize

Maximum prompt sequence length to expect for this model. This affects automatic device mapping but is not a hard limit.

§max_batch_size: usize

Maximum prompt batch size to expect for this model. This affects automatic device mapping but is not a hard limit.

§max_num_images: Option<usize>

Maximum prompt number of images to expect for this model. This affects automatic device mapping but is not a hard limit. Only supported on specific vision models.

§max_image_length: Option<usize>

Maximum expected image size will have this edge length on both edges. This affects automatic device mapping but is not a hard limit. Only supported on specific vision models.

§hf_cache_path: Option<PathBuf>

Cache path for Hugging Face models downloaded locally.

§matformer_config_path: Option<PathBuf>

Path to local Matryoshka Transformer configuration CSV file

§matformer_slice_name: Option<String>

Name of the Matryoshka Transformer slice to use

§

Plain

Select a plain model, without quantization or adapters

Fields

§model_id: String

Model ID to load from. This may be a HF hub repo or a local path.

§tokenizer_json: Option<String>

Path to local tokenizer.json file. If this is specified it is used over any remote file.

§arch: Option<NormalLoaderType>

The architecture of the model.

§dtype: ModelDType

Model data type. Defaults to auto.

§topology: Option<String>

Path to a topology YAML file.

§organization: Option<IsqOrganization>

ISQ organization: default or moqe (Mixture of Quantized Experts: https://arxiv.org/abs/2310.02410).

§write_uqff: Option<PathBuf>

UQFF path to write to.

§from_uqff: Option<String>

UQFF path to load from. If provided, this takes precedence over applying ISQ. Specify multiple files using a semicolon delimiter (;)

§imatrix: Option<PathBuf>

.imatrix file to enhance GGUF quantizations with. Incompatible with --calibration-file/-c

§calibration_file: Option<PathBuf>

Generate and utilize an imatrix to enhance GGUF quantizations. Incompatible with --imatrix/-i

§max_seq_len: usize

Maximum prompt sequence length to expect for this model. This affects automatic device mapping but is not a hard limit.

§max_batch_size: usize

Maximum prompt batch size to expect for this model. This affects automatic device mapping but is not a hard limit.

§hf_cache_path: Option<PathBuf>

Cache path for Hugging Face models downloaded locally

§matformer_config_path: Option<PathBuf>

Path to local Matryoshka Transformer configuration CSV file

§matformer_slice_name: Option<String>

Name of the Matryoshka Transformer slice to use

§

XLora

Select an X-LoRA architecture

Fields

§model_id: Option<String>

Force a base model ID to load from instead of using the ordering file. This may be a HF hub repo or a local path.

§tokenizer_json: Option<String>

Path to local tokenizer.json file. If this is specified it is used over any remote file.

§xlora_model_id: String

Model ID to load X-LoRA from. This may be a HF hub repo or a local path.

§order: String

Ordering JSON file

§tgt_non_granular_index: Option<usize>

Index of completion tokens to generate scalings up until. If this is 1, then there will be one completion token generated before it is cached. This makes the maximum running sequences 1.

§arch: Option<NormalLoaderType>

The architecture of the model.

§dtype: ModelDType

Model data type. Defaults to auto.

§topology: Option<String>

Path to a topology YAML file.

§write_uqff: Option<PathBuf>

UQFF path to write to.

§from_uqff: Option<String>

UQFF path to load from. If provided, this takes precedence over applying ISQ. Specify multiple files using a semicolon delimiter (;).

§max_seq_len: usize

Maximum prompt sequence length to expect for this model. This affects automatic device mapping but is not a hard limit.

§max_batch_size: usize

Maximum prompt batch size to expect for this model. This affects automatic device mapping but is not a hard limit.

§hf_cache_path: Option<PathBuf>

Cache path for Hugging Face models downloaded locally

§

Lora

Select a LoRA architecture

Fields

§model_id: Option<String>

Force a base model ID to load from instead of using the ordering file. This may be a HF hub repo or a local path.

§tokenizer_json: Option<String>

Path to local tokenizer.json file. If this is specified it is used over any remote file.

§adapter_model_id: String

Model ID to load LoRA from. This may be a HF hub repo or a local path.

§arch: Option<NormalLoaderType>

The architecture of the model.

§dtype: ModelDType

Model data type. Defaults to auto.

§topology: Option<String>

Path to a topology YAML file.

§write_uqff: Option<PathBuf>

UQFF path to write to.

§from_uqff: Option<String>

UQFF path to load from. If provided, this takes precedence over applying ISQ. Specify multiple files using a semicolon delimiter (;).

§max_seq_len: usize

Maximum prompt sequence length to expect for this model. This affects automatic device mapping but is not a hard limit.

§max_batch_size: usize

Maximum prompt batch size to expect for this model. This affects automatic device mapping but is not a hard limit.

§hf_cache_path: Option<PathBuf>

Cache path for Hugging Face models downloaded locally

§

GGUF

Select a GGUF model.

Fields

§tok_model_id: Option<String>

tok_model_id is the local or remote model ID where you can find a tokenizer_config.json file. If the chat_template is specified, then it will be treated as a path and used over remote files, removing all remote accesses.

§quantized_model_id: String

Quantized model ID to find the quantized_filename. This may be a HF hub repo or a local path.

§quantized_filename: String

Quantized filename(s). May be a single filename, or use a delimiter of “ “ (a single space) for multiple files.

§dtype: ModelDType

Model data type. Defaults to auto.

§topology: Option<String>

Path to a topology YAML file.

§max_seq_len: usize

Maximum prompt sequence length to expect for this model. This affects automatic device mapping but is not a hard limit.

§max_batch_size: usize

Maximum prompt batch size to expect for this model. This affects automatic device mapping but is not a hard limit.

§

XLoraGGUF

Select a GGUF model with X-LoRA.

Fields

§tok_model_id: Option<String>

tok_model_id is the local or remote model ID where you can find a tokenizer_config.json file. If the chat_template is specified, then it will be treated as a path and used over remote files, removing all remote accesses.

§quantized_model_id: String

Quantized model ID to find the quantized_filename. This may be a HF hub repo or a local path.

§quantized_filename: String

Quantized filename(s). May be a single filename, or use a delimiter of “ “ (a single space) for multiple files.

§xlora_model_id: String

Model ID to load X-LoRA from. This may be a HF hub repo or a local path.

§order: String

Ordering JSON file

§tgt_non_granular_index: Option<usize>

Index of completion tokens to generate scalings up until. If this is 1, then there will be one completion token generated before it is cached. This makes the maximum running sequences 1.

§dtype: ModelDType

Model data type. Defaults to auto.

§topology: Option<String>

Path to a topology YAML file.

§max_seq_len: usize

Maximum prompt sequence length to expect for this model. This affects automatic device mapping but is not a hard limit.

§max_batch_size: usize

Maximum prompt batch size to expect for this model. This affects automatic device mapping but is not a hard limit.

§

LoraGGUF

Select a GGUF model with LoRA.

Fields

§tok_model_id: Option<String>

tok_model_id is the local or remote model ID where you can find a tokenizer_config.json file. If the chat_template is specified, then it will be treated as a path and used over remote files, removing all remote accesses.

§quantized_model_id: String

Quantized model ID to find the quantized_filename. This may be a HF hub repo or a local path.

§quantized_filename: String

Quantized filename(s). May be a single filename, or use a delimiter of “ “ (a single space) for multiple files.

§adapters_model_id: String

Model ID to load LoRA from. This may be a HF hub repo or a local path.

§order: String

Ordering JSON file

§dtype: ModelDType

Model data type. Defaults to auto.

§topology: Option<String>

Path to a topology YAML file.

§max_seq_len: usize

Maximum prompt sequence length to expect for this model. This affects automatic device mapping but is not a hard limit.

§max_batch_size: usize

Maximum prompt batch size to expect for this model. This affects automatic device mapping but is not a hard limit.

§

GGML

Select a GGML model.

Fields

§tok_model_id: String

Model ID to load the tokenizer from. This may be a HF hub repo or a local path.

§tokenizer_json: Option<String>

Path to local tokenizer.json file. If this is specified it is used over any remote file.

§quantized_model_id: String

Quantized model ID to find the quantized_filename. This may be a HF hub repo or a local path.

§quantized_filename: String

Quantized filename.

§gqa: usize

GQA value

§dtype: ModelDType

Model data type. Defaults to auto.

§topology: Option<String>

Path to a topology YAML file.

§max_seq_len: usize

Maximum prompt sequence length to expect for this model. This affects automatic device mapping but is not a hard limit.

§max_batch_size: usize

Maximum prompt batch size to expect for this model. This affects automatic device mapping but is not a hard limit.

§

XLoraGGML

Select a GGML model with X-LoRA.

Fields

§tok_model_id: Option<String>

Model ID to load the tokenizer from. This may be a HF hub repo or a local path.

§tokenizer_json: Option<String>

Path to local tokenizer.json file. If this is specified it is used over any remote file.

§quantized_model_id: String

Quantized model ID to find the quantized_filename. This may be a HF hub repo or a local path.

§quantized_filename: String

Quantized filename.

§xlora_model_id: String

Model ID to load X-LoRA from. This may be a HF hub repo or a local path.

§order: String

Ordering JSON file

§tgt_non_granular_index: Option<usize>

Index of completion tokens to generate scalings up until. If this is 1, then there will be one completion token generated before it is cached. This makes the maximum running sequences 1.

§gqa: usize

GQA value

§dtype: ModelDType

Model data type. Defaults to auto.

§topology: Option<String>

Path to a topology YAML file.

§max_seq_len: usize

Maximum prompt sequence length to expect for this model. This affects automatic device mapping but is not a hard limit.

§max_batch_size: usize

Maximum prompt batch size to expect for this model. This affects automatic device mapping but is not a hard limit.

§

LoraGGML

Select a GGML model with LoRA.

Fields

§tok_model_id: Option<String>

Model ID to load the tokenizer from. This may be a HF hub repo or a local path.

§tokenizer_json: Option<String>

Path to local tokenizer.json file. If this is specified it is used over any remote file.

§quantized_model_id: String

Quantized model ID to find the quantized_filename. This may be a HF hub repo or a local path.

§quantized_filename: String

Quantized filename.

§adapters_model_id: String

Model ID to load LoRA from. This may be a HF hub repo or a local path.

§order: String

Ordering JSON file

§gqa: usize

GQA value

§dtype: ModelDType

Model data type. Defaults to auto.

§topology: Option<String>

Path to a topology YAML file.

§max_seq_len: usize

Maximum prompt sequence length to expect for this model. This affects automatic device mapping but is not a hard limit.

§max_batch_size: usize

Maximum prompt batch size to expect for this model. This affects automatic device mapping but is not a hard limit.

§

VisionPlain

Select a vision plain model, without quantization or adapters

Fields

§model_id: String

Model ID to load from. This may be a HF hub repo or a local path.

§tokenizer_json: Option<String>

Path to local tokenizer.json file. If this is specified it is used over any remote file.

§arch: Option<VisionLoaderType>

The architecture of the model.

§dtype: ModelDType

Model data type. Defaults to auto.

§topology: Option<String>

Path to a topology YAML file.

§write_uqff: Option<PathBuf>

UQFF path to write to.

§from_uqff: Option<String>

UQFF path to load from. If provided, this takes precedence over applying ISQ. Specify multiple files using a semicolon delimiter (;).

§max_edge: Option<u32>

Automatically resize and pad images to this maximum edge length. Aspect ratio is preserved. This is only supported on the Qwen2-VL and Idefics models. Others handle this internally.

§calibration_file: Option<PathBuf>

Generate and utilize an imatrix to enhance GGUF quantizations.

§imatrix: Option<PathBuf>

.cimatrix file to enhance GGUF quantizations with. This must be a .cimatrix file.

§max_seq_len: usize

Maximum prompt sequence length to expect for this model. This affects automatic device mapping but is not a hard limit.

§max_batch_size: usize

Maximum prompt batch size to expect for this model. This affects automatic device mapping but is not a hard limit.

§max_num_images: usize

Maximum prompt number of images to expect for this model. This affects automatic device mapping but is not a hard limit.

§max_image_length: usize

Maximum expected image size will have this edge length on both edges. This affects automatic device mapping but is not a hard limit.

§hf_cache_path: Option<PathBuf>

Cache path for Hugging Face models downloaded locally

§matformer_config_path: Option<PathBuf>

Path to local Matryoshka Transformer configuration CSV file

§matformer_slice_name: Option<String>

Name of the Matryoshka Transformer slice to use

§

DiffusionPlain

Select a diffusion model, without quantization or adapters

Fields

§model_id: String

Model ID to load from. This may be a HF hub repo or a local path.

§arch: DiffusionLoaderType

The architecture of the model.

§dtype: ModelDType

Model data type. Defaults to auto.

§

Speech

Fields

§model_id: String

Model ID to load from. This may be a HF hub repo or a local path.

§dac_model_id: Option<String>

DAC Model ID to load from. If not provided, this is automatically downloaded from the default path for the model. This may be a HF hub repo or a local path.

§arch: SpeechLoaderType

The architecture of the model.

§dtype: ModelDType

Model data type. Defaults to auto.

§

MultiModel

Select multi-model mode with configuration file

Fields

§config: String

Multi-model configuration file path (JSON format)

§default_model_id: Option<String>

Default model ID to use when no model is specified in requests

Trait Implementations§

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impl Clone for ModelSelected

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fn clone(&self) -> ModelSelected

Returns a duplicate of the value. Read more
1.0.0 · Source§

fn clone_from(&mut self, source: &Self)

Performs copy-assignment from source. Read more
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impl Debug for ModelSelected

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fn fmt(&self, f: &mut Formatter<'_>) -> Result<(), Error>

Formats the value using the given formatter. Read more
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impl<'de> Deserialize<'de> for ModelSelected

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fn deserialize<__D>( __deserializer: __D, ) -> Result<ModelSelected, <__D as Deserializer<'de>>::Error>
where __D: Deserializer<'de>,

Deserialize this value from the given Serde deserializer. Read more
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impl FromArgMatches for ModelSelected

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fn from_arg_matches( __clap_arg_matches: &ArgMatches, ) -> Result<ModelSelected, Error>

Instantiate Self from [ArgMatches], parsing the arguments as needed. Read more
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fn from_arg_matches_mut( __clap_arg_matches: &mut ArgMatches, ) -> Result<ModelSelected, Error>

Instantiate Self from [ArgMatches], parsing the arguments as needed. Read more
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fn update_from_arg_matches( &mut self, __clap_arg_matches: &ArgMatches, ) -> Result<(), Error>

Assign values from ArgMatches to self.
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fn update_from_arg_matches_mut<'b>( &mut self, __clap_arg_matches: &mut ArgMatches, ) -> Result<(), Error>

Assign values from ArgMatches to self.
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impl Subcommand for ModelSelected

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fn augment_subcommands<'b>(__clap_app: Command) -> Command

Append to [Command] so it can instantiate Self via [FromArgMatches::from_arg_matches_mut] Read more
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fn augment_subcommands_for_update<'b>(__clap_app: Command) -> Command

Append to [Command] so it can instantiate self via [FromArgMatches::update_from_arg_matches_mut] Read more
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fn has_subcommand(__clap_name: &str) -> bool

Test whether Self can parse a specific subcommand

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unsafe fn deref_mut<'a>(ptr: usize) -> &'a mut T

Mutably dereferences the given pointer. Read more
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unsafe fn drop(ptr: usize)

Drops the object pointed to by the given pointer. Read more
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impl<T> PolicyExt for T
where T: ?Sized,

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fn and<P, B, E>(self, other: P) -> And<T, P>
where T: Policy<B, E>, P: Policy<B, E>,

Create a new Policy that returns [Action::Follow] only if self and other return Action::Follow. Read more
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fn or<P, B, E>(self, other: P) -> Or<T, P>
where T: Policy<B, E>, P: Policy<B, E>,

Create a new Policy that returns [Action::Follow] if either self or other returns Action::Follow. Read more
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impl<T> Same for T

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type Output = T

Should always be Self
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impl<SS, SP> SupersetOf<SS> for SP
where SS: SubsetOf<SP>,

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fn to_subset(&self) -> Option<SS>

The inverse inclusion map: attempts to construct self from the equivalent element of its superset. Read more
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fn is_in_subset(&self) -> bool

Checks if self is actually part of its subset T (and can be converted to it).
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fn to_subset_unchecked(&self) -> SS

Use with care! Same as self.to_subset but without any property checks. Always succeeds.
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fn from_subset(element: &SS) -> SP

The inclusion map: converts self to the equivalent element of its superset.
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impl<T> ToOwned for T
where T: Clone,

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type Owned = T

The resulting type after obtaining ownership.
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fn to_owned(&self) -> T

Creates owned data from borrowed data, usually by cloning. Read more
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fn clone_into(&self, target: &mut T)

Uses borrowed data to replace owned data, usually by cloning. Read more
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impl<T> TryClone for T
where T: Clone,

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fn try_clone(&self) -> Result<T, Error>

Clones self, possibly returning an error.
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impl<T, U> TryFrom<U> for T
where U: Into<T>,

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type Error = Infallible

The type returned in the event of a conversion error.
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fn try_from(value: U) -> Result<T, <T as TryFrom<U>>::Error>

Performs the conversion.
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impl<T, U> TryInto<U> for T
where U: TryFrom<T>,

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type Error = <U as TryFrom<T>>::Error

The type returned in the event of a conversion error.
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fn try_into(self) -> Result<U, <U as TryFrom<T>>::Error>

Performs the conversion.
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impl<V, T> VZip<V> for T
where V: MultiLane<T>,

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fn vzip(self) -> V

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impl<T> WithSubscriber for T

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fn with_subscriber<S>(self, subscriber: S) -> WithDispatch<Self>
where S: Into<Dispatch>,

Attaches the provided Subscriber to this type, returning a [WithDispatch] wrapper. Read more
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fn with_current_subscriber(self) -> WithDispatch<Self>

Attaches the current default Subscriber to this type, returning a [WithDispatch] wrapper. Read more
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impl<T> DeserializeOwned for T
where T: for<'de> Deserialize<'de>,

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impl<T> ErasedDestructor for T
where T: 'static,

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impl<T> ErasedDestructor for T
where T: 'static,

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impl<T> Ungil for T
where T: Send,