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distilabel:
version: 1.0.0
pipeline:
name: farming
description: null
steps:
- step:
name: load_data
input_mappings: {}
output_mappings: {}
batch_size: 64
data:
- input: animal welfare from a Family Farming perspective
- input: animal welfare from a Agribusiness perspective
- input: animal welfare from a Permaculture perspective
- input: animal welfare from a Agroforestery perspective
- input: animal welfare from a Conventional Farming perspective
- input: economic growth from a Family Farming perspective
- input: economic growth from a Agribusiness perspective
- input: economic growth from a Permaculture perspective
- input: economic growth from a Agroforestery perspective
- input: economic growth from a Conventional Farming perspective
- input: land from a Family Farming perspective
- input: land from a Agribusiness perspective
- input: land from a Permaculture perspective
- input: land from a Agroforestery perspective
- input: land from a Conventional Farming perspective
- input: resources from a Family Farming perspective
- input: resources from a Agribusiness perspective
- input: resources from a Permaculture perspective
- input: resources from a Agroforestery perspective
- input: resources from a Conventional Farming perspective
- input: efficiency from a Family Farming perspective
- input: efficiency from a Agribusiness perspective
- input: efficiency from a Permaculture perspective
- input: efficiency from a Agroforestery perspective
- input: efficiency from a Conventional Farming 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://hh1rkuymnetmkw9m.eu-west-1.aws.endpoints.huggingface.cloud
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 farming.
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 farming.
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://hh1rkuymnetmkw9m.eu-west-1.aws.endpoints.huggingface.cloud
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<PROMPT>\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\
<PROMPT>\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<PROMPT>\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<PROMPT>\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#:
<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://hh1rkuymnetmkw9m.eu-west-1.aws.endpoints.huggingface.cloud
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: farming
dataset_workspace: admin
api_url: https://argilla-farming.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
|