| distilabel: |
| version: 1.5.3 |
| pipeline: |
| name: generate |
| description: null |
| steps: |
| - step: |
| name: load_data_from_hub_0 |
| resources: |
| replicas: 1 |
| cpus: null |
| gpus: null |
| memory: null |
| resources: null |
| input_mappings: {} |
| output_mappings: |
| Job Role Description: anchor |
| use_cache: false |
| batch_size: 50 |
| repo_id: dnth/ssf-dataset |
| split: train |
| config: null |
| revision: null |
| streaming: false |
| num_examples: 10 |
| 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_from_hub_0 |
| - step: |
| name: hard_triplets |
| resources: |
| replicas: 1 |
| cpus: null |
| gpus: null |
| memory: null |
| resources: null |
| input_mappings: {} |
| output_mappings: {} |
| use_cache: true |
| input_batch_size: 100 |
| llm: |
| generation_kwargs: |
| temperature: 0.6 |
| max_new_tokens: 512 |
| use_offline_batch_generation: false |
| offline_batch_generation_block_until_done: null |
| jobs_ids: null |
| model: gpt-4.1-mini |
| base_url: https://api.openai.com/v1 |
| default_headers: null |
| max_retries: 6 |
| timeout: 120 |
| structured_output: null |
| type_info: |
| module: distilabel.models.llms.openai |
| name: OpenAILLM |
| group_generations: false |
| add_raw_output: true |
| add_raw_input: true |
| num_generations: 1 |
| use_default_structured_output: false |
| triplet: true |
| action: paraphrase |
| hard_negative: true |
| context: "\n\n## Task Overview\nYou are tasked with generating realistic job\ |
| \ descriptions based on Singapore SkillsFuture Framework job descriptions.\ |
| \ Your goal is to create both positive and a few negative examples for training\ |
| \ a retrieval model.\n\n## Input Format\nYou will receive a job description\ |
| \ from the Singapore SkillsFuture Framework containing:\n- Job title (e.g.,\ |
| \ Audit Associate/Audit Assistant Associate)\n- Role responsibilities and\ |
| \ duties\n- Work environment and supervision structure\n- Required skills\ |
| \ and attributes\n- Professional conduct expectations\n\nThe text is a job\ |
| \ description from the Singapore SkillsFuture Framework. Your task is to generate\ |
| \ a realistic positive variation and a few hard negative variation.\n\n\n\ |
| Hard negative is a job description that is similar in some ways but is ultimately\ |
| \ incorrect for the given job. It must not be a simple paraphrase of a different,\ |
| \ unrelated job.\n\nChoose from these strategies for hard negatives:\n1. **Different\ |
| \ seniority level:** (e.g., Senior vs. Junior)\n2. **Different function:**\ |
| \ (e.g., Business Valuation vs. Risk Management)\n3. **Different technology\ |
| \ stack:** (e.g., Python/AWS vs. Scala/Azure for a Data Engineer role)\n4.\ |
| \ **Different job title, same responsibilities:** (e.g., \"Web Developer\"\ |
| \ vs. \"Frontend Engineer\")\n5. **Different industry jargon:** (e.g., \"\ |
| Project Manager\" in Tech vs. \"Project Manager\" in Construction)\n6. **Broad\ |
| \ vs. specialized role:** (e.g., a \"Data Scientist\" role for a \"Machine\ |
| \ Learning Engineer\" positive)\n\nExample:\nJob Role: \"Data Analyst\"\n\ |
| Positive: \"As a Data Analyst, you will interpret data and analyze results\ |
| \ using statistical techniques. You will work to develop and implement data\ |
| \ collection systems and other strategies that optimize statistical efficiency\ |
| \ and quality.\"\n\n\nNegative: \"As a Senior Data Analyst, you will lead\ |
| \ a team of junior analysts, manage end-to-end data projects, and present\ |
| \ insights to key stakeholders to drive business strategy.\"\n\n \ |
| \ \"As a Financial Analyst, you will analyze financial data to provide insights\ |
| \ into business performance and support strategic decision-making.\"\n\n \ |
| \ \"As a Healthcare Data Analyst, you will manage electronic health\ |
| \ records and assist in clinical research data analysis.\"\n\n\nMake sure\ |
| \ to mix a few strategies in one negative query. you could also use different\ |
| \ strategies that is not mentioned above as long as it is a hard negative.\n\ |
| Makesure to have a few negatives in one query like in the example given and\ |
| \ make a new line for each new query.\nThe Job description of the negatives\ |
| \ should give the real job description to a real job title.\nThe query should\ |
| \ always include the job role and start with \"The <job role>\".\n" |
| 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: max_new_tokens |
| optional: true |
| - name: logprobs |
| optional: true |
| - name: top_logprobs |
| optional: true |
| - name: echo |
| optional: true |
| - name: frequency_penalty |
| optional: true |
| - name: presence_penalty |
| optional: true |
| - name: temperature |
| optional: true |
| - name: top_p |
| optional: true |
| - name: stop |
| optional: true |
| - name: response_format |
| optional: true |
| - name: extra_body |
| optional: true |
| - 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: base_url |
| optional: true |
| description: The base URL to use for the OpenAI API requests. |
| - name: api_key |
| optional: true |
| description: The API key to authenticate the requests to the OpenAI API. |
| - name: default_headers |
| optional: true |
| description: The default headers to use for the OpenAI API requests. |
| - name: max_retries |
| optional: true |
| description: The maximum number of times to retry the request to the API |
| before failing. |
| - name: timeout |
| optional: true |
| description: The maximum time in seconds to wait for a response from the |
| 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: distilabel.steps.tasks.sentence_transformers |
| name: GenerateSentencePair |
| name: hard_triplets |
| - step: |
| name: easy_triplets |
| resources: |
| replicas: 1 |
| cpus: null |
| gpus: null |
| memory: null |
| resources: null |
| input_mappings: {} |
| output_mappings: {} |
| use_cache: true |
| input_batch_size: 100 |
| llm: |
| generation_kwargs: |
| temperature: 0.6 |
| max_new_tokens: 512 |
| use_offline_batch_generation: false |
| offline_batch_generation_block_until_done: null |
| jobs_ids: null |
| model: gpt-4.1-mini |
| base_url: https://api.openai.com/v1 |
| default_headers: null |
| max_retries: 6 |
| timeout: 120 |
| structured_output: null |
| type_info: |
| module: distilabel.models.llms.openai |
| name: OpenAILLM |
| group_generations: false |
| add_raw_output: true |
| add_raw_input: true |
| num_generations: 1 |
| use_default_structured_output: false |
| triplet: true |
| action: paraphrase |
| hard_negative: false |
| context: "\n\n\n## Task Overview\nYou are tasked with generating realistic job\ |
| \ descriptions based on Singapore SkillsFuture Framework job descriptions.\ |
| \ Your goal is to create both positive and a few negative examples for training\ |
| \ a retrieval model.\n\n## Input Format\nYou will receive a job description\ |
| \ from the Singapore SkillsFuture Framework containing:\n- Job title (e.g.,\ |
| \ Audit Associate/Audit Assistant Associate)\n- Role responsibilities and\ |
| \ duties\n- Work environment and supervision structure\n- Required skills\ |
| \ and attributes\n- Professional conduct expectations\n\nThe text is a job\ |
| \ description from the Singapore SkillsFuture Framework. Your task is to generate\ |
| \ a realistic positive variation and a few easy negative variation.\n\nEasy\ |
| \ negative is a job description and title that is completely irrelevant to\ |
| \ the original job's industry, domain, or skills. It should be easy for the\ |
| \ model to distinguish from the positive document.\n\nChoose from these strategies\ |
| \ for easy negatives:\n1. Completely different industry (e.g., IT vs. Retail).\n\ |
| 2. Unrelated skills and responsibilities.\n3. Completely different job function\ |
| \ (e.g., Software Engineering vs. Human Resources).\n\nExample:\nJob Role:\ |
| \ \"Data Analyst\"\n\nPositive: \"As a Data Analyst, you will interpret data\ |
| \ and analyze results using statistical techniques. You will work to develop\ |
| \ and implement data collection systems and other strategies that optimize\ |
| \ statistical efficiency and quality.\"\n\nEasy Negative : \"As a Retail Manager,\ |
| \ you will be responsible for overseeing daily store operations, managing\ |
| \ inventory, and training staff to provide excellent customer service.\"\n\ |
| \n \"As a Human Resources Assistant, you will provide administrative\ |
| \ support to the HR department, assist with recruitment and onboarding processes,\ |
| \ and maintain employee records.\"\n\n \"As a Professional\ |
| \ Chef, you will be responsible for managing kitchen staff, creating new menu\ |
| \ items, and ensuring all dishes are prepared to the highest quality standards.\"\ |
| \n\n\nMake sure, that there is a variety of easy negatives across the dataset,\ |
| \ using different strategies as outlined above.\nMakesure to have a few negatives\ |
| \ in one query like in the example given.\nThe query should always include\ |
| \ the job role and start with \"The <job role>\".\n" |
| 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: max_new_tokens |
| optional: true |
| - name: logprobs |
| optional: true |
| - name: top_logprobs |
| optional: true |
| - name: echo |
| optional: true |
| - name: frequency_penalty |
| optional: true |
| - name: presence_penalty |
| optional: true |
| - name: temperature |
| optional: true |
| - name: top_p |
| optional: true |
| - name: stop |
| optional: true |
| - name: response_format |
| optional: true |
| - name: extra_body |
| optional: true |
| - 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: base_url |
| optional: true |
| description: The base URL to use for the OpenAI API requests. |
| - name: api_key |
| optional: true |
| description: The API key to authenticate the requests to the OpenAI API. |
| - name: default_headers |
| optional: true |
| description: The default headers to use for the OpenAI API requests. |
| - name: max_retries |
| optional: true |
| description: The maximum number of times to retry the request to the API |
| before failing. |
| - name: timeout |
| optional: true |
| description: The maximum time in seconds to wait for a response from the |
| 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: distilabel.steps.tasks.sentence_transformers |
| name: GenerateSentencePair |
| name: easy_triplets |
| - step: |
| name: easy_keywords |
| resources: |
| replicas: 1 |
| cpus: null |
| gpus: null |
| memory: null |
| resources: null |
| input_mappings: {} |
| output_mappings: {} |
| use_cache: true |
| input_batch_size: 100 |
| llm: |
| generation_kwargs: |
| temperature: 0.6 |
| max_new_tokens: 512 |
| use_offline_batch_generation: false |
| offline_batch_generation_block_until_done: null |
| jobs_ids: null |
| model: gpt-4.1-mini |
| base_url: https://api.openai.com/v1 |
| default_headers: null |
| max_retries: 6 |
| timeout: 120 |
| structured_output: null |
| type_info: |
| module: distilabel.models.llms.openai |
| name: OpenAILLM |
| group_generations: false |
| add_raw_output: true |
| add_raw_input: true |
| num_generations: 1 |
| use_default_structured_output: false |
| triplet: true |
| action: query |
| hard_negative: false |
| context: ' |
| |
| The text below is a job description from the Singapore SkillsFuture Framework. |
| Your task is to generate two things: |
| |
| 1. A list of key skills for the job (the positive). |
| |
| 2. A list of unrelated skills (the easy negative). |
| |
| |
| An **easy negative** is a set of keywords that is completely unrelated to |
| the job description and its industry. It should be easy for the model to distinguish |
| and serves to give the model a clear sense of what is definitively irrelevant. |
| |
| |
| Example: |
| |
| Job Role: "Network Engineer" |
| |
| Positive Keywords: "Network administration, Cisco, firewall management, VPN" |
| |
| Easy Negative Keywords: "Retail inventory management, customer service, cash |
| handling, visual merchandising" |
| |
| ' |
| 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: max_new_tokens |
| optional: true |
| - name: logprobs |
| optional: true |
| - name: top_logprobs |
| optional: true |
| - name: echo |
| optional: true |
| - name: frequency_penalty |
| optional: true |
| - name: presence_penalty |
| optional: true |
| - name: temperature |
| optional: true |
| - name: top_p |
| optional: true |
| - name: stop |
| optional: true |
| - name: response_format |
| optional: true |
| - name: extra_body |
| optional: true |
| - 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: base_url |
| optional: true |
| description: The base URL to use for the OpenAI API requests. |
| - name: api_key |
| optional: true |
| description: The API key to authenticate the requests to the OpenAI API. |
| - name: default_headers |
| optional: true |
| description: The default headers to use for the OpenAI API requests. |
| - name: max_retries |
| optional: true |
| description: The maximum number of times to retry the request to the API |
| before failing. |
| - name: timeout |
| optional: true |
| description: The maximum time in seconds to wait for a response from the |
| 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: distilabel.steps.tasks.sentence_transformers |
| name: GenerateSentencePair |
| name: easy_keywords |
| - step: |
| name: hard_keywords |
| resources: |
| replicas: 1 |
| cpus: null |
| gpus: null |
| memory: null |
| resources: null |
| input_mappings: {} |
| output_mappings: {} |
| use_cache: true |
| input_batch_size: 100 |
| llm: |
| generation_kwargs: |
| temperature: 0.6 |
| max_new_tokens: 512 |
| use_offline_batch_generation: false |
| offline_batch_generation_block_until_done: null |
| jobs_ids: null |
| model: gpt-4.1-mini |
| base_url: https://api.openai.com/v1 |
| default_headers: null |
| max_retries: 6 |
| timeout: 120 |
| structured_output: null |
| type_info: |
| module: distilabel.models.llms.openai |
| name: OpenAILLM |
| group_generations: false |
| add_raw_output: true |
| add_raw_input: true |
| num_generations: 1 |
| use_default_structured_output: false |
| triplet: true |
| action: query |
| hard_negative: true |
| context: ' |
| |
| The text below is a job description from the Singapore SkillsFuture Framework. |
| Your task is to generate two things: |
| |
| 1. A list of key skills for the job (the positive). |
| |
| 2. A list of unrelated skills (the easy negative). |
| |
| |
| An **easy negative** is a set of keywords that is completely unrelated to |
| the job description and its industry. It should be easy for the model to distinguish |
| and serves to give the model a clear sense of what is definitively irrelevant. |
| |
| |
| Example: |
| |
| Job Role: "Network Engineer" |
| |
| Positive Keywords: "Network administration, Cisco, firewall management, VPN" |
| |
| Easy Negative Keywords: "Retail inventory management, customer service, cash |
| handling, visual merchandising" |
| |
| ' |
| 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: max_new_tokens |
| optional: true |
| - name: logprobs |
| optional: true |
| - name: top_logprobs |
| optional: true |
| - name: echo |
| optional: true |
| - name: frequency_penalty |
| optional: true |
| - name: presence_penalty |
| optional: true |
| - name: temperature |
| optional: true |
| - name: top_p |
| optional: true |
| - name: stop |
| optional: true |
| - name: response_format |
| optional: true |
| - name: extra_body |
| optional: true |
| - 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: base_url |
| optional: true |
| description: The base URL to use for the OpenAI API requests. |
| - name: api_key |
| optional: true |
| description: The API key to authenticate the requests to the OpenAI API. |
| - name: default_headers |
| optional: true |
| description: The default headers to use for the OpenAI API requests. |
| - name: max_retries |
| optional: true |
| description: The maximum number of times to retry the request to the API |
| before failing. |
| - name: timeout |
| optional: true |
| description: The maximum time in seconds to wait for a response from the |
| 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: distilabel.steps.tasks.sentence_transformers |
| name: GenerateSentencePair |
| name: hard_keywords |
| connections: |
| - from: load_data_from_hub_0 |
| to: |
| - hard_triplets |
| - easy_triplets |
| - easy_keywords |
| - hard_keywords |
| - from: hard_triplets |
| to: [] |
| - from: easy_triplets |
| to: [] |
| - from: easy_keywords |
| to: [] |
| - from: hard_keywords |
| to: [] |
| routing_batch_functions: [] |
| type_info: |
| module: distilabel.pipeline.local |
| name: Pipeline |
| requirements: [] |
|
|
