CServeV2RecipeOutput.md

CServeV2RecipeOutput

Inputs to start deployment

Properties

Name	Type	Description	Notes
model	str
max_model_len	int
is_embedding_model	bool		[default to False]
tokenizer	str
tensor_parallel_size	int
pipeline_parallel_size	int
gpu_mem_util	float		[default to 0.95]
block_size	int		[default to 16]
swap_space	int		[default to 0]
quantization	str
dtype	str		[default to 'auto']
cache_dtype	str		[default to 'auto']
max_num_seqs	int		[default to 256]
eager_execution	bool		[default to True]
use_flashinfer	bool		[default to False]
offloading_num	float		[default to 0]
spec_draft_model	str
spec_tokens	int
spec_prompt_lookup_max	int
spec_prompt_lookup_min	int
use_prefix_caching	bool		[default to False]
use_chunked_prefill	bool		[default to False]
chunked_prefill_size	int
max_seq_len_to_capture	int		[default to 8192]
distributed_executor_backend	str		[default to 'mp']
spec_max_batch_size	int
spec_max_seq_len	int
num_scheduler_steps	int		[default to 1]

Example

from platform_api_python_client.models.c_serve_v2_recipe_output import CServeV2RecipeOutput

# TODO update the JSON string below
json = "{}"
# create an instance of CServeV2RecipeOutput from a JSON string
c_serve_v2_recipe_output_instance = CServeV2RecipeOutput.from_json(json)
# print the JSON string representation of the object
print(CServeV2RecipeOutput.to_json())

# convert the object into a dict
c_serve_v2_recipe_output_dict = c_serve_v2_recipe_output_instance.to_dict()
# create an instance of CServeV2RecipeOutput from a dict
c_serve_v2_recipe_output_from_dict = CServeV2RecipeOutput.from_dict(c_serve_v2_recipe_output_dict)

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