distilabel: version: 1.4.0 pipeline: name: image_generation_pipeline description: null steps: - step: name: load_data resources: replicas: 1 cpus: null gpus: null memory: null resources: null input_mappings: {} output_mappings: {} batch_size: 50 repo_id: fal/imgsys-results split: train config: null revision: null streaming: false num_examples: 2 storage_options: null runtime_parameters_info: - name: resources runtime_parameters_info: - name: replicas optional: true description: The number of replicas for the step. - name: cpus optional: true description: The number of CPUs assigned to each step replica. - name: gpus optional: true description: The number of GPUs assigned to each step replica. - name: memory optional: true description: The memory in bytes required for each step replica. - name: resources optional: true description: A dictionary containing names of custom resources and the number of those resources required for each step replica. - name: batch_size optional: true description: The number of rows that will contain the batches generated by the step. - name: repo_id optional: false description: The Hugging Face Hub repository ID of the dataset to load. - name: split optional: true description: The split of the dataset to load. Defaults to 'train'. - name: config optional: true description: The configuration of the dataset to load. This is optional and only needed if the dataset has multiple configurations. - name: revision optional: true description: The revision of the dataset to load. Defaults to the latest revision. - name: streaming optional: true description: Whether to load the dataset in streaming mode or not. Defaults to False. - name: num_examples optional: true description: The number of examples to load from the dataset. By default will load all examples. type_info: module: distilabel.steps.generators.huggingface name: LoadDataFromHub name: load_data - step: name: flux_schnell resources: replicas: 1 cpus: null gpus: null memory: null resources: null input_mappings: {} output_mappings: {} input_batch_size: 50 llm: use_magpie_template: false magpie_pre_query_template: null generation_kwargs: {} use_offline_batch_generation: false offline_batch_generation_block_until_done: null jobs_ids: null model_id: black-forest-labs/FLUX.1-schnell endpoint_name: null endpoint_namespace: null base_url: null tokenizer_id: null model_display_name: null structured_output: null type_info: module: __main__ name: InferenceEndpointsImageLLM group_generations: false add_raw_output: true add_raw_input: true num_generations: 1 use_default_structured_output: false runtime_parameters_info: - name: resources runtime_parameters_info: - name: replicas optional: true description: The number of replicas for the step. - name: cpus optional: true description: The number of CPUs assigned to each step replica. - name: gpus optional: true description: The number of GPUs assigned to each step replica. - name: memory optional: true description: The memory in bytes required for each step replica. - name: resources optional: true description: A dictionary containing names of custom resources and the number of those resources required for each step replica. - name: input_batch_size optional: true description: The number of rows that will contain the batches processed by the step. - name: llm runtime_parameters_info: - name: generation_kwargs description: The kwargs to be propagated to either `generate` or `agenerate` methods within each `LLM`. keys: [] - name: use_offline_batch_generation optional: true description: Whether to use the `offline_batch_generate` method to generate the responses. - name: offline_batch_generation_block_until_done optional: true description: If provided, then polling will be done until the `ofline_batch_generate` method is able to retrieve the results. The value indicate the time to wait between each polling. - name: endpoint_name optional: true description: The name of the Inference Endpoint to use for the LLM. - name: endpoint_namespace optional: true description: The namespace of the Inference Endpoint to use for the LLM. - name: base_url optional: true description: The base URL to use for the Inference Endpoints API requests. - name: api_key optional: true description: The API key to authenticate the requests to the Inference Endpoints API. - name: structured_output optional: true description: The structured output format to use across all the generations. - name: add_raw_output optional: true description: Whether to include the raw output of the LLM in the key `raw_output_` of the `distilabel_metadata` dictionary output column - name: add_raw_input optional: true description: Whether to include the raw input of the LLM in the key `raw_input_` of the `distilabel_metadata` dictionary column - name: num_generations optional: true description: The number of generations to be produced per input. type_info: module: __main__ name: ImageGeneration name: flux_schnell - step: name: flux_dev resources: replicas: 1 cpus: null gpus: null memory: null resources: null input_mappings: {} output_mappings: {} input_batch_size: 50 llm: use_magpie_template: false magpie_pre_query_template: null generation_kwargs: {} use_offline_batch_generation: false offline_batch_generation_block_until_done: null jobs_ids: null model_id: black-forest-labs/FLUX.1-dev endpoint_name: null endpoint_namespace: null base_url: null tokenizer_id: null model_display_name: null structured_output: null type_info: module: __main__ name: InferenceEndpointsImageLLM group_generations: false add_raw_output: true add_raw_input: true num_generations: 1 use_default_structured_output: false runtime_parameters_info: - name: resources runtime_parameters_info: - name: replicas optional: true description: The number of replicas for the step. - name: cpus optional: true description: The number of CPUs assigned to each step replica. - name: gpus optional: true description: The number of GPUs assigned to each step replica. - name: memory optional: true description: The memory in bytes required for each step replica. - name: resources optional: true description: A dictionary containing names of custom resources and the number of those resources required for each step replica. - name: input_batch_size optional: true description: The number of rows that will contain the batches processed by the step. - name: llm runtime_parameters_info: - name: generation_kwargs description: The kwargs to be propagated to either `generate` or `agenerate` methods within each `LLM`. keys: [] - name: use_offline_batch_generation optional: true description: Whether to use the `offline_batch_generate` method to generate the responses. - name: offline_batch_generation_block_until_done optional: true description: If provided, then polling will be done until the `ofline_batch_generate` method is able to retrieve the results. The value indicate the time to wait between each polling. - name: endpoint_name optional: true description: The name of the Inference Endpoint to use for the LLM. - name: endpoint_namespace optional: true description: The namespace of the Inference Endpoint to use for the LLM. - name: base_url optional: true description: The base URL to use for the Inference Endpoints API requests. - name: api_key optional: true description: The API key to authenticate the requests to the Inference Endpoints API. - name: structured_output optional: true description: The structured output format to use across all the generations. - name: add_raw_output optional: true description: Whether to include the raw output of the LLM in the key `raw_output_` of the `distilabel_metadata` dictionary output column - name: add_raw_input optional: true description: Whether to include the raw input of the LLM in the key `raw_input_` of the `distilabel_metadata` dictionary column - name: num_generations optional: true description: The number of generations to be produced per input. type_info: module: __main__ name: ImageGeneration name: flux_dev - step: name: sdxl resources: replicas: 1 cpus: null gpus: null memory: null resources: null input_mappings: {} output_mappings: {} input_batch_size: 50 llm: use_magpie_template: false magpie_pre_query_template: null generation_kwargs: {} use_offline_batch_generation: false offline_batch_generation_block_until_done: null jobs_ids: null model_id: stabilityai/stable-diffusion-xl-base-1.0 endpoint_name: null endpoint_namespace: null base_url: null tokenizer_id: null model_display_name: null structured_output: null type_info: module: __main__ name: InferenceEndpointsImageLLM group_generations: false add_raw_output: true add_raw_input: true num_generations: 1 use_default_structured_output: false runtime_parameters_info: - name: resources runtime_parameters_info: - name: replicas optional: true description: The number of replicas for the step. - name: cpus optional: true description: The number of CPUs assigned to each step replica. - name: gpus optional: true description: The number of GPUs assigned to each step replica. - name: memory optional: true description: The memory in bytes required for each step replica. - name: resources optional: true description: A dictionary containing names of custom resources and the number of those resources required for each step replica. - name: input_batch_size optional: true description: The number of rows that will contain the batches processed by the step. - name: llm runtime_parameters_info: - name: generation_kwargs description: The kwargs to be propagated to either `generate` or `agenerate` methods within each `LLM`. keys: [] - name: use_offline_batch_generation optional: true description: Whether to use the `offline_batch_generate` method to generate the responses. - name: offline_batch_generation_block_until_done optional: true description: If provided, then polling will be done until the `ofline_batch_generate` method is able to retrieve the results. The value indicate the time to wait between each polling. - name: endpoint_name optional: true description: The name of the Inference Endpoint to use for the LLM. - name: endpoint_namespace optional: true description: The namespace of the Inference Endpoint to use for the LLM. - name: base_url optional: true description: The base URL to use for the Inference Endpoints API requests. - name: api_key optional: true description: The API key to authenticate the requests to the Inference Endpoints API. - name: structured_output optional: true description: The structured output format to use across all the generations. - name: add_raw_output optional: true description: Whether to include the raw output of the LLM in the key `raw_output_` of the `distilabel_metadata` dictionary output column - name: add_raw_input optional: true description: Whether to include the raw input of the LLM in the key `raw_input_` of the `distilabel_metadata` dictionary column - name: num_generations optional: true description: The number of generations to be produced per input. type_info: module: __main__ name: ImageGeneration name: sdxl - step: name: opendalle resources: replicas: 1 cpus: null gpus: null memory: null resources: null input_mappings: {} output_mappings: {} input_batch_size: 50 llm: use_magpie_template: false magpie_pre_query_template: null generation_kwargs: {} use_offline_batch_generation: false offline_batch_generation_block_until_done: null jobs_ids: null model_id: dataautogpt3/OpenDalleV1.1 endpoint_name: null endpoint_namespace: null base_url: null tokenizer_id: null model_display_name: null structured_output: null type_info: module: __main__ name: InferenceEndpointsImageLLM group_generations: false add_raw_output: true add_raw_input: true num_generations: 1 use_default_structured_output: false runtime_parameters_info: - name: resources runtime_parameters_info: - name: replicas optional: true description: The number of replicas for the step. - name: cpus optional: true description: The number of CPUs assigned to each step replica. - name: gpus optional: true description: The number of GPUs assigned to each step replica. - name: memory optional: true description: The memory in bytes required for each step replica. - name: resources optional: true description: A dictionary containing names of custom resources and the number of those resources required for each step replica. - name: input_batch_size optional: true description: The number of rows that will contain the batches processed by the step. - name: llm runtime_parameters_info: - name: generation_kwargs description: The kwargs to be propagated to either `generate` or `agenerate` methods within each `LLM`. keys: [] - name: use_offline_batch_generation optional: true description: Whether to use the `offline_batch_generate` method to generate the responses. - name: offline_batch_generation_block_until_done optional: true description: If provided, then polling will be done until the `ofline_batch_generate` method is able to retrieve the results. The value indicate the time to wait between each polling. - name: endpoint_name optional: true description: The name of the Inference Endpoint to use for the LLM. - name: endpoint_namespace optional: true description: The namespace of the Inference Endpoint to use for the LLM. - name: base_url optional: true description: The base URL to use for the Inference Endpoints API requests. - name: api_key optional: true description: The API key to authenticate the requests to the Inference Endpoints API. - name: structured_output optional: true description: The structured output format to use across all the generations. - name: add_raw_output optional: true description: Whether to include the raw output of the LLM in the key `raw_output_` of the `distilabel_metadata` dictionary output column - name: add_raw_input optional: true description: Whether to include the raw input of the LLM in the key `raw_input_` of the `distilabel_metadata` dictionary column - name: num_generations optional: true description: The number of generations to be produced per input. type_info: module: __main__ name: ImageGeneration name: opendalle - step: name: group_columns_0 resources: replicas: 1 cpus: null gpus: null memory: null resources: null input_mappings: {} output_mappings: {} input_batch_size: 50 columns: - image - model_name output_columns: - images - models runtime_parameters_info: - name: resources runtime_parameters_info: - name: replicas optional: true description: The number of replicas for the step. - name: cpus optional: true description: The number of CPUs assigned to each step replica. - name: gpus optional: true description: The number of GPUs assigned to each step replica. - name: memory optional: true description: The memory in bytes required for each step replica. - name: resources optional: true description: A dictionary containing names of custom resources and the number of those resources required for each step replica. - name: input_batch_size optional: true description: The number of rows that will contain the batches processed by the step. type_info: module: distilabel.steps.columns.group name: GroupColumns name: group_columns_0 - step: name: keep_columns_0 resources: replicas: 1 cpus: null gpus: null memory: null resources: null input_mappings: {} output_mappings: {} input_batch_size: 50 columns: - prompt - models - images runtime_parameters_info: - name: resources runtime_parameters_info: - name: replicas optional: true description: The number of replicas for the step. - name: cpus optional: true description: The number of CPUs assigned to each step replica. - name: gpus optional: true description: The number of GPUs assigned to each step replica. - name: memory optional: true description: The memory in bytes required for each step replica. - name: resources optional: true description: A dictionary containing names of custom resources and the number of those resources required for each step replica. - name: input_batch_size optional: true description: The number of rows that will contain the batches processed by the step. type_info: module: distilabel.steps.columns.keep name: KeepColumns name: keep_columns_0 connections: - from: load_data to: - flux_schnell - flux_dev - sdxl - opendalle - from: flux_schnell to: - group_columns_0 - from: flux_dev to: - group_columns_0 - from: sdxl to: - group_columns_0 - from: opendalle to: - group_columns_0 - from: group_columns_0 to: - keep_columns_0 - from: keep_columns_0 to: [] routing_batch_functions: - step: load_data description: Sample 2 steps from the list of downstream steps. type_info: module: distilabel.pipeline.routing_batch_function name: sample_n_steps kwargs: n: 2 type_info: module: distilabel.pipeline.local name: Pipeline requirements: []