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		Accelerator
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		Constant
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		Generator
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		Full Train Step
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		Eval Step
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		Train Step
		UpdatedSeptember 4, 2025		
 Create Llama Generator
Description
Create Streaming Llama Generator Session.

Input parameters
 ONNX in : object, llama generator session.
 ONNX in : object, llama generator session.
 Β Parameters :Β cluster,
Β Parameters :Β cluster,
 use_position_idsΒ :Β boolean, enables the use of explicit position IDs for the input tokens.
 use_position_idsΒ :Β boolean, enables the use of explicit position IDs for the input tokens. temperatureΒ :Β float, controls randomness in the generation process.
 temperatureΒ :Β float, controls randomness in the generation process. repetition_penaltyΒ :Β float, penalizes repeated tokens to reduce looping or redundant text.
 repetition_penaltyΒ :Β float, penalizes repeated tokens to reduce looping or redundant text. max_length :Β integer, maximum number of tokens in the generated output sequence.
 max_length :Β integer, maximum number of tokens in the generated output sequence. ngram_size :Β integer, size of n-grams tracked to prevent repetition.
 ngram_size :Β integer, size of n-grams tracked to prevent repetition.
 llama_decoder_session : integer, reference to an active ONNX inference session of the LLaMA decoder model.
 llama_decoder_session : integer, reference to an active ONNX inference session of the LLaMA decoder model.
 
			Output parameters
 ONNX out : object, llama generator session.
 ONNX out : object, llama generator session.
Example
All these exemples are snippets PNG, you can drop these Snippet onto the block diagram and get the depicted code added to your VI (Do not forget to install Deep Learning library to run it).
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