| 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_<TASK_NAME>` | |
| 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_<TASK_NAME>` | |
| 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_<TASK_NAME>` | |
| 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_<TASK_NAME>` | |
| 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_<TASK_NAME>` | |
| 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_<TASK_NAME>` | |
| 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_<TASK_NAME>` | |
| 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_<TASK_NAME>` | |
| 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: [] | |