Gemma3¶
Gemma3는 텍스트와 이미지를 입력으로 처리하고 텍스트를 출력으로 생성하는 멀티모달 모델로, 사전 학습된 변형과 지침 조정된 변형 모두에 대해 오픈 웨이트를 제공합니다. RBLN NPU는 Optimum RBLN을 사용하여 Gemma3 모델 추론을 가속화할 수 있습니다.
API Reference¶
Classes¶
RBLNGemma3ForConditionalGeneration
¶
Bases: RBLNModel
Functions¶
from_model(model, config=None, rbln_config=None, model_save_dir=None, subfolder='', **kwargs)
classmethod
¶
Converts and compiles a pre-trained HuggingFace library model into a RBLN model. This method performs the actual model conversion and compilation process.
Parameters:
Name | Type | Description | Default |
---|---|---|---|
model
|
PreTrainedModel
|
The PyTorch model to be compiled. The object must be an instance of the HuggingFace transformers PreTrainedModel class. |
required |
config
|
Optional[PretrainedConfig]
|
The configuration object associated with the model. |
None
|
rbln_config
|
Optional[Union[RBLNModelConfig, Dict]]
|
Configuration for RBLN model compilation and runtime.
This can be provided as a dictionary or an instance of the model's configuration class (e.g., |
None
|
kwargs
|
Any
|
Additional keyword arguments. Arguments with the prefix |
{}
|
The method performs the following steps:
- Compiles the PyTorch model into an optimized RBLN graph
- Configures the model for the specified NPU device
- Creates the necessary runtime objects if requested
- Saves the compiled model and configurations
Returns:
Type | Description |
---|---|
RBLNModel
|
A RBLN model instance ready for inference on RBLN NPU devices. |
from_pretrained(model_id, export=None, rbln_config=None, **kwargs)
classmethod
¶
The from_pretrained()
function is utilized in its standard form as in the HuggingFace transformers library.
User can use this function to load a pre-trained model from the HuggingFace library and convert it to a RBLN model to be run on RBLN NPUs.
Parameters:
Name | Type | Description | Default |
---|---|---|---|
model_id
|
Union[str, Path]
|
The model id of the pre-trained model to be loaded. It can be downloaded from the HuggingFace model hub or a local path, or a model id of a compiled model using the RBLN Compiler. |
required |
export
|
Optional[bool]
|
A boolean flag to indicate whether the model should be compiled. If None, it will be determined based on the existence of the compiled model files in the model_id. |
None
|
rbln_config
|
Optional[Union[Dict, RBLNModelConfig]]
|
Configuration for RBLN model compilation and runtime.
This can be provided as a dictionary or an instance of the model's configuration class (e.g., |
None
|
kwargs
|
Any
|
Additional keyword arguments. Arguments with the prefix |
{}
|
Returns:
Type | Description |
---|---|
RBLNModel
|
A RBLN model instance ready for inference on RBLN NPU devices. |
save_pretrained(save_directory, push_to_hub=False, **kwargs)
¶
Saves a model and its configuration file to a directory, so that it can be re-loaded using the
[~optimum.rbln.modeling_base.RBLNBaseModel.from_pretrained
] class method.
Parameters:
Name | Type | Description | Default |
---|---|---|---|
save_directory
|
Union[str, Path]
|
Directory where to save the model file. |
required |
push_to_hub
|
bool
|
Whether or not to push your model to the HuggingFace model hub after saving it. |
False
|
RBLNGemma3ForCausalLM
¶
Bases: RBLNDecoderOnlyModelForCausalLM
The Gemma3 Model transformer with a language modeling head (linear layer) on top.
This model inherits from [RBLNDecoderOnlyModelForCausalLM
]. Check the superclass documentation for the generic methods the library implements for all its models.
A class to convert and run pre-trained transformers based Gemma3ForCausalLM model on RBLN devices. It implements the methods to convert a pre-trained transformers Gemma3ForCausalLM model into a RBLN transformer model by: - transferring the checkpoint weights of the original into an optimized RBLN graph, - compiling the resulting graph using the RBLN compiler.
Functions¶
generate(input_ids, attention_mask=None, max_length=None, **kwargs)
¶
The generate function is utilized in its standard form as in the HuggingFace transformers library. User can use this function to generate text from the model.
Parameters:
Name | Type | Description | Default |
---|---|---|---|
input_ids
|
LongTensor
|
The input ids to the model. |
required |
attention_mask
|
Optional[LongTensor]
|
The attention mask to the model. |
None
|
max_length
|
Optional[int]
|
The maximum length of the generated text. |
None
|
kwargs
|
Additional arguments passed to the generate function. See the HuggingFace transformers documentation for more details. |
{}
|
from_pretrained(model_id, export=None, rbln_config=None, **kwargs)
classmethod
¶
The from_pretrained()
function is utilized in its standard form as in the HuggingFace transformers library.
User can use this function to load a pre-trained model from the HuggingFace library and convert it to a RBLN model to be run on RBLN NPUs.
Parameters:
Name | Type | Description | Default |
---|---|---|---|
model_id
|
Union[str, Path]
|
The model id of the pre-trained model to be loaded. It can be downloaded from the HuggingFace model hub or a local path, or a model id of a compiled model using the RBLN Compiler. |
required |
export
|
Optional[bool]
|
A boolean flag to indicate whether the model should be compiled. If None, it will be determined based on the existence of the compiled model files in the model_id. |
None
|
rbln_config
|
Optional[Union[Dict, RBLNModelConfig]]
|
Configuration for RBLN model compilation and runtime.
This can be provided as a dictionary or an instance of the model's configuration class (e.g., |
None
|
kwargs
|
Any
|
Additional keyword arguments. Arguments with the prefix |
{}
|
Returns:
Type | Description |
---|---|
RBLNModel
|
A RBLN model instance ready for inference on RBLN NPU devices. |
save_pretrained(save_directory, push_to_hub=False, **kwargs)
¶
Saves a model and its configuration file to a directory, so that it can be re-loaded using the
[~optimum.rbln.modeling_base.RBLNBaseModel.from_pretrained
] class method.
Parameters:
Name | Type | Description | Default |
---|---|---|---|
save_directory
|
Union[str, Path]
|
Directory where to save the model file. |
required |
push_to_hub
|
bool
|
Whether or not to push your model to the HuggingFace model hub after saving it. |
False
|
from_model(model, config=None, rbln_config=None, model_save_dir=None, subfolder='', **kwargs)
classmethod
¶
Converts and compiles a pre-trained HuggingFace library model into a RBLN model. This method performs the actual model conversion and compilation process.
Parameters:
Name | Type | Description | Default |
---|---|---|---|
model
|
PreTrainedModel
|
The PyTorch model to be compiled. The object must be an instance of the HuggingFace transformers PreTrainedModel class. |
required |
config
|
Optional[PretrainedConfig]
|
The configuration object associated with the model. |
None
|
rbln_config
|
Optional[Union[RBLNModelConfig, Dict]]
|
Configuration for RBLN model compilation and runtime.
This can be provided as a dictionary or an instance of the model's configuration class (e.g., |
None
|
kwargs
|
Any
|
Additional keyword arguments. Arguments with the prefix |
{}
|
The method performs the following steps:
- Compiles the PyTorch model into an optimized RBLN graph
- Configures the model for the specified NPU device
- Creates the necessary runtime objects if requested
- Saves the compiled model and configurations
Returns:
Type | Description |
---|---|
RBLNModel
|
A RBLN model instance ready for inference on RBLN NPU devices. |
Classes¶
RBLNGemma3ForCausalLMConfig
¶
Bases: RBLNDecoderOnlyModelForCausalLMConfig
Functions¶
__init__(use_position_ids=None, use_attention_mask=None, prefill_chunk_size=None, image_prefill_chunk_size=None, **kwargs)
¶
Parameters:
Name | Type | Description | Default |
---|---|---|---|
use_position_ids
|
Optional[bool]
|
Whether or not to use |
None
|
use_attention_mask
|
Optional[bool]
|
Whether or not to use |
None
|
prefill_chunk_size
|
Optional[int]
|
The chunk size used during the prefill phase for processing input sequences. Defaults to 256. Must be a positive integer divisible by 64. Affects prefill performance and memory usage. |
None
|
image_prefill_chunk_size
|
Optional[int]
|
The chunk size used during the prefill phase for
processing images. This config is used when |
None
|
kwargs
|
Any
|
Additional arguments passed to the parent |
{}
|
Raises:
Type | Description |
---|---|
ValueError
|
If |
load(path, **kwargs)
classmethod
¶
Load a RBLNModelConfig from a path.
Parameters:
Name | Type | Description | Default |
---|---|---|---|
path
|
str
|
Path to the RBLNModelConfig file or directory containing the config file. |
required |
kwargs
|
Any
|
Additional keyword arguments to override configuration values. Keys starting with 'rbln_' will have the prefix removed and be used to update the configuration. |
{}
|
Returns:
Name | Type | Description |
---|---|---|
RBLNModelConfig |
RBLNModelConfig
|
The loaded configuration instance. |
Note
This method loads the configuration from the specified path and applies any provided overrides. If the loaded configuration class doesn't match the expected class, a warning will be logged.
RBLNGemma3ForConditionalGenerationConfig
¶
Bases: RBLNModelConfig
Functions¶
__init__(batch_size=None, vision_tower=None, language_model=None, **kwargs)
¶
Parameters:
Name | Type | Description | Default |
---|---|---|---|
batch_size
|
Optional[int]
|
The batch size for inference. Defaults to 1. |
None
|
vision_tower
|
Optional[RBLNModelConfig]
|
Configuration for the vision encoder component. |
None
|
language_model
|
Optional[RBLNModelConfig]
|
Configuration for the language model component. |
None
|
kwargs
|
Any
|
Additional arguments passed to the parent RBLNModelConfig. |
{}
|
Raises:
Type | Description |
---|---|
ValueError
|
If |
load(path, **kwargs)
classmethod
¶
Load a RBLNModelConfig from a path.
Parameters:
Name | Type | Description | Default |
---|---|---|---|
path
|
str
|
Path to the RBLNModelConfig file or directory containing the config file. |
required |
kwargs
|
Any
|
Additional keyword arguments to override configuration values. Keys starting with 'rbln_' will have the prefix removed and be used to update the configuration. |
{}
|
Returns:
Name | Type | Description |
---|---|---|
RBLNModelConfig |
RBLNModelConfig
|
The loaded configuration instance. |
Note
This method loads the configuration from the specified path and applies any provided overrides. If the loaded configuration class doesn't match the expected class, a warning will be logged.