size_categories:100K<n<1M format:parquet modality:text library:datasets library:pandas library:mlcroissant library:polars region:us
---
configs:
- config_name: all
  data_files:
  - split: train
    path: all/train-*
- config_name: CodeAlpaca-20k
  data_files:
  - split: train
    path: CodeAlpaca-20k/train-*
- config_name: Everything_Instruct
  data_files:
  - split: train
    path: Everything_Instruct/train-*
- config_name: OpenMathInstruct-2
  data_files:
  - split: train
    path: OpenMathInstruct-2/train-*
- config_name: alpaca-cleaned
  data_files:
  - split: train
    path: alpaca-cleaned/train-*
- config_name: databricks-dolly-15k
  data_files:
  - split: train
    path: databricks-dolly-15k/train-*
- config_name: ifeval-like-data
  data_files:
  - split: train
    path: ifeval-like-data/train-*
- config_name: instruct
  data_files:
  - split: train
    path: instruct/train-*
- config_name: symbolic-instruction-tuning
  data_files:
  - split: train
    path: symbolic-instruction-tuning/train-*

dataset_info:
- config_name: all
  features:
  - name: question
    dtype: string
  - name: answer
    dtype: string
  - name: problem_source
    dtype: string
  splits:
  - name: train
    num_bytes: 64999827.0
    num_examples: 66000
  download_size: 37271721
  dataset_size: 64999827.0
- config_name: CodeAlpaca-20k
  features:
  - name: question
    dtype: string
  - name: answer
    dtype: string
  - name: problem_source
    dtype: string
  splits:
  - name: train
    num_bytes: 3180550
    num_examples: 10000
  download_size: 1624304
  dataset_size: 3180550
- config_name: Everything_Instruct
  features:
  - name: question
    dtype: string
  - name: answer
    dtype: string
  - name: problem_source
    dtype: string
  splits:
  - name: train
    num_bytes: 13896632
    num_examples: 8000
  download_size: 7787151
  dataset_size: 13896632
- config_name: OpenMathInstruct-2
  features:
  - name: problem_source
    dtype: string
  - name: question
    dtype: string
  - name: answer
    dtype: string
  splits:
  - name: train
    num_bytes: 20167248
    num_examples: 15000
  download_size: 9481648
  dataset_size: 20167248
- config_name: alpaca-cleaned
  features:
  - name: question
    dtype: string
  - name: answer
    dtype: string
  - name: problem_source
    dtype: string
  splits:
  - name: train
    num_bytes: 7667260
    num_examples: 10000
  download_size: 4493432
  dataset_size: 7667260
- config_name: databricks-dolly-15k
  features:
  - name: question
    dtype: string
  - name: answer
    dtype: string
  - name: problem_source
    dtype: string
  splits:
  - name: train
    num_bytes: 8088998
    num_examples: 10000
  download_size: 5105496
  dataset_size: 8088998
- config_name: ifeval-like-data
  features:
  - name: question
    dtype: string
  - name: answer
    dtype: string
  - name: problem_source
    dtype: string
  splits:
  - name: train
    num_bytes: 3281176
    num_examples: 3000
  download_size: 1545615
  dataset_size: 3281176
- config_name: instruct
  features:
  - name: question
    dtype: string
  - name: answer
    dtype: string
  - name: problem_source
    dtype: string
  splits:
  - name: train
    num_bytes: 5515217
    num_examples: 5000
  download_size: 3030073
  dataset_size: 5515217
- config_name: symbolic-instruction-tuning
  features:
  - name: question
    dtype: string
  - name: answer
    dtype: string
  - name: problem_source
    dtype: string
  splits:
  - name: train
    num_bytes: 3202746
    num_examples: 5000
  download_size: 1935836
  dataset_size: 3202746

---


A dataset with all you need to fine-tune a model (sft). The combination of all the subsets is in "all".

