distilabel: version: 1.0.1 pipeline: name: farming description: null steps: - step: name: load_data input_mappings: {} output_mappings: {} batch_size: 64 data: - input: punctures from a Retro bikes perspective runtime_parameters_info: - name: batch_size optional: true description: The number of rows that will contain the batches generated by the step. type_info: module: distilabel.steps.generators.data name: LoadDataFromDicts name: load_data - step: name: self-instruct input_mappings: {} output_mappings: {} input_batch_size: 8 llm: generation_kwargs: {} model_id: null endpoint_name: null endpoint_namespace: null base_url: https://api-inference.huggingface.co/models/HuggingFaceH4/zephyr-7b-beta tokenizer_id: null model_display_name: null use_openai_client: false type_info: module: distilabel.llms.huggingface.inference_endpoints name: InferenceEndpointsLLM group_generations: false num_generations: 1 num_instructions: 5 criteria_for_query_generation: 'Incorporate a diverse range of verbs, avoiding repetition. Ensure queries are compatible with AI model''s text generation functions and are limited to 1-2 sentences. Design queries to be self-contained and standalone. Blend interrogative (e.g., "What is the significance of x?") and imperative (e.g., "Detail the process of x.") styles.' application_description: 'You are an AI assistant than generates queries around the domain of Bicycle maintenance. Your should not expect basic but profound questions from your users. The queries should reflect a diversity of vision and economic positions and political positions. The queries may know about different methods of Bicycle maintenance. The queries can be positioned politically, economically, socially, or practically. Also take into account the impact of diverse causes on diverse domains.' runtime_parameters_info: - 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: max_new_tokens optional: true description: the maximum number of new tokens that the model will generate. Defaults to `128`. - name: frequency_penalty optional: true description: the repetition penalty to use for the generation. Defaults to `0.0`. Only applies if `use_openai_client=True`. - name: presence_penalty optional: true description: the presence penalty to use for the generation. Defaults to `0.0`. Only applies if `use_openai_client=True`. - name: repetition_penalty optional: true description: the repetition penalty to use for the generation. Defaults to `None`. Only applies if `use_openai_client=False`. - name: temperature optional: true description: the temperature to use for the generation. Defaults to `1.0`. - name: do_sample optional: true description: whether to use sampling for the generation. Defaults to `False`. Only applies if `use_openai_client=False`. - name: top_k optional: true description: the top-k value to use for the generation. Defaults to `0.8`, since neither `0.0` nor `1.0` are valid values in TGI. - name: top_p optional: true description: the top-p value to use for the generation. Defaults to `1.0`. - name: typical_p optional: true description: the typical-p value to use for the generation. Defaults to `0.5`. - 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: num_generations optional: true description: The number of generations to be produced per input. type_info: module: distilabel.steps.tasks.self_instruct name: SelfInstruct name: self-instruct - step: name: evol_instruction_complexity input_mappings: instruction: question output_mappings: {} input_batch_size: 8 llm: generation_kwargs: {} model_id: null endpoint_name: null endpoint_namespace: null base_url: https://api-inference.huggingface.co/models/HuggingFaceH4/zephyr-7b-beta tokenizer_id: null model_display_name: null use_openai_client: false type_info: module: distilabel.llms.huggingface.inference_endpoints name: InferenceEndpointsLLM group_generations: false num_generations: 1 num_evolutions: 2 store_evolutions: true generate_answers: false include_original_instruction: true mutation_templates: CONSTRAINTS: "I want you act as a Prompt Rewriter.\n\nYour objective is to\ \ rewrite a given prompt into a more complex version to make those famous\ \ AI systems (e.g., chatgpt and GPT4) a bit harder to handle.\n\nBut the\ \ rewritten prompt must be reasonable and must be understood and responded\ \ by humans.\n\nYour rewriting cannot omit the non-text parts such as the\ \ table and code in #The Given Prompt#:. Also, please do not omit the input\ \ in #The Given Prompt#.\n\nYou SHOULD complicate the given prompt using\ \ the following method: \nPlease add one more constraints/requirements into\ \ '#The Given Prompt#'\n\nYou should try your best not to make the #Rewritten\ \ Prompt# become verbose, #Rewritten Prompt# can only add 10 to 20 words\ \ into #The Given Prompt#.\n\n'#The Given Prompt#', '#Rewritten Prompt#',\ \ 'given prompt' and 'rewritten prompt' are not allowed to appear in #Rewritten\ \ Prompt#\n\n#The Given Prompt#:\n\n#Rewritten Prompt#:\n\n" DEEPENING: "I want you act as a Prompt Rewriter.\n\nYour objective is to rewrite\ \ a given prompt into a more complex version to make those famous AI systems\ \ (e.g., chatgpt and GPT4) a bit harder to handle.\n\nBut the rewritten\ \ prompt must be reasonable and must be understood and responded by humans.\n\ \nYour rewriting cannot omit the non-text parts such as the table and code\ \ in #The Given Prompt#:. Also, please do not omit the input in #The Given\ \ Prompt#.\n\nYou SHOULD complicate the given prompt using the following\ \ method: \nIf #The Given Prompt# contains inquiries about certain issues,\ \ the depth and breadth of the inquiry can be increased.\n\nYou should try\ \ your best not to make the #Rewritten Prompt# become verbose, #Rewritten\ \ Prompt# can only add 10 to 20 words into #The Given Prompt#.\n\n'#The\ \ Given Prompt#', '#Rewritten Prompt#', 'given prompt' and 'rewritten prompt'\ \ are not allowed to appear in #Rewritten Prompt#\n\n#The Given Prompt#:\n\ \n#Rewritten Prompt#:\n\n" CONCRETIZING: "I want you act as a Prompt Rewriter.\n\nYour objective is to\ \ rewrite a given prompt into a more complex version to make those famous\ \ AI systems (e.g., chatgpt and GPT4) a bit harder to handle.\n\nBut the\ \ rewritten prompt must be reasonable and must be understood and responded\ \ by humans.\n\nYour rewriting cannot omit the non-text parts such as the\ \ table and code in #The Given Prompt#:. Also, please do not omit the input\ \ in #The Given Prompt#.\n\nYou SHOULD complicate the given prompt using\ \ the following method: \nPlease replace general concepts with more specific\ \ concepts.\n\nYou should try your best not to make the #Rewritten Prompt#\ \ become verbose, #Rewritten Prompt# can only add 10 to 20 words into #The\ \ Given Prompt#.\n\n'#The Given Prompt#', '#Rewritten Prompt#', 'given prompt'\ \ and 'rewritten prompt' are not allowed to appear in #Rewritten Prompt#\n\ \n#The Given Prompt#:\n\n#Rewritten Prompt#:\n\n" INCREASED_REASONING_STEPS: "I want you act as a Prompt Rewriter.\n\nYour objective\ \ is to rewrite a given prompt into a more complex version to make those\ \ famous AI systems (e.g., chatgpt and GPT4) a bit harder to handle.\n\n\ But the rewritten prompt must be reasonable and must be understood and responded\ \ by humans.\n\nYour rewriting cannot omit the non-text parts such as the\ \ table and code in #The Given Prompt#:. Also, please do not omit the input\ \ in #The Given Prompt#.\n\nYou SHOULD complicate the given prompt using\ \ the following method: \nIf #The Given Prompt# can be solved with just\ \ a few simple thinking processes, you can rewrite it to explicitly request\ \ multiple-step reasoning.\n\nYou should try your best not to make the #Rewritten\ \ Prompt# become verbose, #Rewritten Prompt# can only add 10 to 20 words\ \ into #The Given Prompt#.\n\n'#The Given Prompt#', '#Rewritten Prompt#',\ \ 'given prompt' and 'rewritten prompt' are not allowed to appear in #Rewritten\ \ Prompt#\n\n#The Given Prompt#:\n\n#Rewritten Prompt#:\n\n" BREADTH: 'I want you act as a Prompt Creator. Your goal is to draw inspiration from the #Given Prompt# to create a brand new prompt. This new prompt should belong to the same domain as the #Given Prompt# but be even more rare. The LENGTH and complexity of the #Created Prompt# should be similar to that of the #Given Prompt#. The #Created Prompt# must be reasonable and must be understood and responded by humans. ''#Given Prompt#'', ''#Created Prompt#'', ''given prompt'' and ''created prompt'' are not allowed to appear in #Created Prompt# #Given Prompt#: #Created Prompt#: ' seed: 42 runtime_parameters_info: - 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: max_new_tokens optional: true description: the maximum number of new tokens that the model will generate. Defaults to `128`. - name: frequency_penalty optional: true description: the repetition penalty to use for the generation. Defaults to `0.0`. Only applies if `use_openai_client=True`. - name: presence_penalty optional: true description: the presence penalty to use for the generation. Defaults to `0.0`. Only applies if `use_openai_client=True`. - name: repetition_penalty optional: true description: the repetition penalty to use for the generation. Defaults to `None`. Only applies if `use_openai_client=False`. - name: temperature optional: true description: the temperature to use for the generation. Defaults to `1.0`. - name: do_sample optional: true description: whether to use sampling for the generation. Defaults to `False`. Only applies if `use_openai_client=False`. - name: top_k optional: true description: the top-k value to use for the generation. Defaults to `0.8`, since neither `0.0` nor `1.0` are valid values in TGI. - name: top_p optional: true description: the top-p value to use for the generation. Defaults to `1.0`. - name: typical_p optional: true description: the typical-p value to use for the generation. Defaults to `0.5`. - 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: num_generations optional: true description: The number of generations to be produced per input. - name: seed optional: true description: As `numpy` is being used in order to randomly pick a mutation method, then is nice to seed a random seed. type_info: module: distilabel.steps.tasks.evol_instruct.base name: EvolInstruct name: evol_instruction_complexity - step: name: expand_columns input_mappings: {} output_mappings: {} input_batch_size: 50 columns: instructions: question runtime_parameters_info: - 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.expand name: ExpandColumns name: expand_columns - step: name: clean_numbered_list input_mappings: {} output_mappings: {} input_batch_size: 50 runtime_parameters_info: - name: input_batch_size optional: true description: The number of rows that will contain the batches processed by the step. type_info: module: domain name: CleanNumberedList name: clean_numbered_list - step: name: expand_columns_evolved input_mappings: {} output_mappings: {} input_batch_size: 50 columns: evolved_instructions: evolved_questions runtime_parameters_info: - 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.expand name: ExpandColumns name: expand_columns_evolved - step: name: domain_expert input_mappings: instruction: evolved_questions output_mappings: generation: domain_expert_answer input_batch_size: 8 llm: generation_kwargs: {} model_id: null endpoint_name: null endpoint_namespace: null base_url: https://api-inference.huggingface.co/models/HuggingFaceH4/zephyr-7b-beta tokenizer_id: null model_display_name: null use_openai_client: false type_info: module: distilabel.llms.huggingface.inference_endpoints name: InferenceEndpointsLLM group_generations: false num_generations: 1 runtime_parameters_info: - 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: max_new_tokens optional: true description: the maximum number of new tokens that the model will generate. Defaults to `128`. - name: frequency_penalty optional: true description: the repetition penalty to use for the generation. Defaults to `0.0`. Only applies if `use_openai_client=True`. - name: presence_penalty optional: true description: the presence penalty to use for the generation. Defaults to `0.0`. Only applies if `use_openai_client=True`. - name: repetition_penalty optional: true description: the repetition penalty to use for the generation. Defaults to `None`. Only applies if `use_openai_client=False`. - name: temperature optional: true description: the temperature to use for the generation. Defaults to `1.0`. - name: do_sample optional: true description: whether to use sampling for the generation. Defaults to `False`. Only applies if `use_openai_client=False`. - name: top_k optional: true description: the top-k value to use for the generation. Defaults to `0.8`, since neither `0.0` nor `1.0` are valid values in TGI. - name: top_p optional: true description: the top-p value to use for the generation. Defaults to `1.0`. - name: typical_p optional: true description: the typical-p value to use for the generation. Defaults to `0.5`. - 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: num_generations optional: true description: The number of generations to be produced per input. type_info: module: domain name: DomainExpert name: domain_expert - step: name: keep_columns input_mappings: {} output_mappings: {} input_batch_size: 50 columns: - model_name - evolved_questions - domain_expert_answer runtime_parameters_info: - 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.keep name: KeepColumns name: keep_columns - step: name: text_generation_to_argilla input_mappings: instruction: evolved_questions generation: domain_expert_answer output_mappings: {} input_batch_size: 50 dataset_name: bicycle_maintenance dataset_workspace: admin api_url: https://burtenshaw-bicycle-maintenance-argilla-space.hf.space runtime_parameters_info: - name: input_batch_size optional: true description: The number of rows that will contain the batches processed by the step. - name: dataset_name optional: false description: The name of the dataset in Argilla. - name: dataset_workspace optional: true description: The workspace where the dataset will be created in Argilla. Defaultsto `None` which means it will be created in the default workspace. - name: api_url optional: true description: The base URL to use for the Argilla API requests. - name: api_key optional: true description: The API key to authenticate the requests to the Argilla API. type_info: module: distilabel.steps.argilla.text_generation name: TextGenerationToArgilla name: text_generation_to_argilla connections: - from: load_data to: - self-instruct - from: self-instruct to: - expand_columns - from: evol_instruction_complexity to: - expand_columns_evolved - from: expand_columns to: - clean_numbered_list - from: clean_numbered_list to: - evol_instruction_complexity - from: expand_columns_evolved to: - domain_expert - from: domain_expert to: - keep_columns - from: keep_columns to: - text_generation_to_argilla - from: text_generation_to_argilla to: [] type_info: module: distilabel.pipeline.local name: Pipeline