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Upload pipeline.yaml with huggingface_hub
Browse files- pipeline.yaml +62 -0
pipeline.yaml
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distilabel:
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version: 1.0.0.b0
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pipeline:
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name: DEITA
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description: ''
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steps:
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- step:
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name: load_data
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input_mappings: {}
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output_mappings: {}
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batch_size: 100
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repo_id: distilabel-internal-testing/deita-after-embeddings
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split: train
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config: null
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runtime_parameters_info:
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- name: repo_id
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optional: false
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description: The Hugging Face Hub repository ID of the dataset to load.
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- name: split
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optional: true
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description: The split of the dataset to load. Defaults to 'train'.
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- name: config
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optional: true
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description: The configuration of the dataset to load. This is optional and
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only needed if the dataset has multiple configurations.
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type_info:
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module: distilabel.steps.generators.huggingface
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name: LoadHubDataset
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name: load_data
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- step:
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name: deita_filtering
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input_mappings: {}
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output_mappings: {}
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input_batch_size: 50
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data_budget: 500
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diversity_threshold: 0.04
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normalize_embeddings: false
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runtime_parameters_info:
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- name: data_budget
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optional: false
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description: The desired size of the dataset after filtering.
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- name: diversity_threshold
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optional: true
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description: If a row has a cosine distance with respect to it's nearest neighbor
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greater than this value, it will be included in the filtered dataset.
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- name: normalize_embeddings
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optional: true
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description: Whether to normalize the embeddings before computing the cosine
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distance.
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type_info:
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module: distilabel.steps.deita
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name: DeitaFiltering
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name: deita_filtering
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connections:
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- from: load_data
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to:
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- deita_filtering
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- from: deita_filtering
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to: []
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type_info:
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module: distilabel.pipeline.local
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name: Pipeline
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