distilabel: version: 1.4.1 pipeline: name: pipeline-translate-demo description: Pipeline translate demo steps: - step: name: load_dataset resources: replicas: 1 cpus: null gpus: null memory: null resources: null input_mappings: {} output_mappings: {} use_cache: true batch_size: 50 repo_id: mteb/emotion split: train config: null revision: null streaming: false num_examples: null 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_dataset - step: name: translate_en2vi_demo resources: replicas: 1 cpus: null gpus: 2 memory: null resources: null input_mappings: {} output_mappings: {} use_cache: true input_batch_size: 50 llm: cuda_devices: auto disable_cuda_device_placement: false use_magpie_template: false magpie_pre_query_template: null generation_kwargs: temperature: 0.0 top_p: 1.0 max_new_tokens: 4096 use_offline_batch_generation: false offline_batch_generation_block_until_done: null jobs_ids: null model: CohereForAI/aya-23-35B dtype: bfloat16 trust_remote_code: false quantization: null revision: null tokenizer: CohereForAI/aya-23-35B tokenizer_mode: auto tokenizer_revision: null skip_tokenizer_init: false chat_template: null seed: 0 extra_kwargs: tensor_parallel_size: 2 distributed_executor_backend: ray gpu_memory_utilization: 0.9 max_model_len: 4096 structured_output: null type_info: module: distilabel.llms.vllm name: vLLM group_generations: false add_raw_output: true add_raw_input: true num_generations: 1 use_default_structured_output: false system_prompt: You are a professional translator with a deep understanding of both the English and Vietnamese languages. You possess a high level of proficiency in translating between these languages, ensuring that the translation retains both the meaning and cultural nuances of the original text. With a thorough knowledge of grammar, syntax, and colloquialisms in both languages, you can accurately and naturally translate the following from English to Vietnamese while maintaining its intended tone and context. Your work is known for its precision and attention to detail, making your translations clear and effective for a wide audience. use_system_prompt: false template: 'Translate the following from English to Vietnamese: {{text}} TRANSLATED VERSION IN VIETNAMESE IS: ' columns: - text 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: cuda_devices optional: true description: A list with the ID of the CUDA devices to be used. - name: disable_cuda_device_placement optional: true description: Whether to disable the CUDA device placement logic or not. - name: generation_kwargs description: The kwargs to be propagated to either `generate` or `agenerate` methods within each `LLM`. keys: - name: max_new_tokens optional: true description: the maximum number of new tokens that the model will generate. Defaults to `128`. - name: presence_penalty optional: true description: the presence penalty to use for the generation. Defaults to `0.0`. - name: frequency_penalty optional: true description: the repetition penalty to use for the generation. Defaults to `0.0`. - name: repetition_penalty optional: true description: the repetition penalty to use for the generation Defaults to `1.0`. - name: temperature optional: true description: the temperature to use for the generation. Defaults to `0.1`. - name: top_p optional: true description: the top-p value to use for the generation. Defaults to `1.0`. - name: top_k optional: true description: the top-k value to use for the generation. Defaults to `0`. - name: min_p optional: true description: the minimum probability to use for the generation. Defaults to `0.0`. - name: stop optional: true description: a list of strings that will be used to stop the generation when found. Defaults to `None`. - name: stop_token_ids optional: true description: a list of token ids that will be used to stop the generation when found. Defaults to `None`. - name: include_stop_str_in_output optional: true description: whether to include the stop string in the output. Defaults to `False`. - name: logits_processors optional: true description: a list of functions to process the logits before sampling. Defaults to `None`. - name: extra_sampling_params optional: true description: dictionary with additional arguments to be passed to the `SamplingParams` class from `vllm`. - 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: extra_kwargs optional: true description: 'Additional dictionary of keyword arguments that will be passed to the `vLLM` class of `vllm` library. See all the supported arguments at: https://github.com/vllm-project/vllm/blob/main/vllm/entrypoints/llm.py' - 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: TranslateText name: translate_en2vi_demo - step: name: rename_columns resources: replicas: 1 cpus: null gpus: null memory: null resources: null input_mappings: {} output_mappings: {} use_cache: true input_batch_size: 50 columns_map: text: og_text label: label label_text: label_text vietnamese_version: text 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: __main__ name: RenameColumns name: rename_columns - step: name: keep_columns resources: replicas: 1 cpus: null gpus: null memory: null resources: null input_mappings: {} output_mappings: {} use_cache: true input_batch_size: 50 columns: - text - label - label_text - og_text 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 connections: - from: load_dataset to: - translate_en2vi_demo - from: translate_en2vi_demo to: - rename_columns - from: rename_columns to: - keep_columns - from: keep_columns to: [] routing_batch_functions: [] type_info: module: distilabel.pipeline.local name: Pipeline requirements: []