LongChat-Lines / README.md
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metadata
configs:
  - config_name: default
    data_files:
      - split: '100'
        path: data/100-*
      - split: '150'
        path: data/150-*
      - split: '175'
        path: data/175-*
      - split: '200'
        path: data/200-*
      - split: '250'
        path: data/250-*
      - split: '300'
        path: data/300-*
      - split: '400'
        path: data/400-*
      - split: '500'
        path: data/500-*
      - split: '600'
        path: data/600-*
      - split: '680'
        path: data/680-*
      - split: '750'
        path: data/750-*
      - split: '850'
        path: data/850-*
      - split: '950'
        path: data/950-*
      - split: '1100'
        path: data/1100-*
dataset_info:
  features:
    - name: expected_number
      dtype: int64
    - name: num_lines
      dtype: int64
    - name: token_size
      dtype: int64
    - name: prompt
      dtype: string
  splits:
    - name: '100'
      num_bytes: 275673
      num_examples: 50
    - name: '150'
      num_bytes: 400446
      num_examples: 50
    - name: '175'
      num_bytes: 463159
      num_examples: 50
    - name: '200'
      num_bytes: 525856
      num_examples: 50
    - name: '250'
      num_bytes: 650643
      num_examples: 50
    - name: '300'
      num_bytes: 775800
      num_examples: 50
    - name: '400'
      num_bytes: 1025288
      num_examples: 50
    - name: '500'
      num_bytes: 1276039
      num_examples: 50
    - name: '600'
      num_bytes: 1524627
      num_examples: 50
    - name: '680'
      num_bytes: 1724325
      num_examples: 50
    - name: '750'
      num_bytes: 1899422
      num_examples: 50
    - name: '850'
      num_bytes: 2149220
      num_examples: 50
    - name: '950'
      num_bytes: 2398398
      num_examples: 50
    - name: '1100'
      num_bytes: 2772556
      num_examples: 50
  download_size: 7270406
  dataset_size: 17861452

image/png

Dataset Card for "LongChat-Lines"

This dataset is was used to evaluate the performance of model finetuned to operate on longer contexts. It is based on a task template proposed by LMSys to evaluate attention to arbitrary points in the context. See the full details at https;//github.com/abacusai/Long-Context.