| --- |
| license: apache-2.0 |
| task_categories: |
| - question-answering |
| - text-generation |
| annotations_creators: |
| - crowdsourced |
| - expert-generated |
| language: |
| - amh |
| - arb |
| - ary |
| - ars |
| - acq |
| - arz |
| - apc |
| - ben |
| - ceb |
| - dan |
| - deu |
| - ell |
| - eng |
| - eus |
| - fil |
| - fin |
| - fra |
| - gle |
| - guj |
| - hat |
| - hau |
| - hin |
| - hun |
| - ibo |
| - ind |
| - ita |
| - jav |
| - jpn |
| - kan |
| - kir |
| - kor |
| - kur |
| - lit |
| - mal |
| - mar |
| - mlg |
| - msa |
| - mya |
| - nep |
| - nld |
| - nso |
| - nya |
| - pan |
| - pes |
| - pol |
| - por |
| - pus |
| - rus |
| - sin |
| - sna |
| - snd |
| - som |
| - spa |
| - sqi |
| - srp |
| - sun |
| - swa |
| - swe |
| - tam |
| - tel |
| - tha |
| - tur |
| - ukr |
| - urd |
| - vie |
| - wol |
| - xho |
| - yor |
| - zho |
| - zul |
| language_creators: |
| - crowdsourced |
| - expert-generated |
| multilinguality: |
| - multilingual |
| size_categories: |
| - 100K<n<1M |
| --- |
| |
| [CohereForAI/aya_dataset](https://huggingface.co/datasets/CohereForAI/aya_dataset) in ChatML format, ready to use in [HuggingFace TRL's SFT Trainer](https://huggingface.co/docs/trl/main/en/sft_trainer). |
|
|
| Python code used for conversion: |
|
|
| ```python |
| from datasets import load_dataset |
| from transformers import AutoTokenizer |
| |
| tokenizer = AutoTokenizer.from_pretrained("Felladrin/Llama-160M-Chat-v1") |
| |
| dataset = load_dataset("CohereForAI/aya_dataset", split="train") |
| |
| def format(columns): |
| messages = [ |
| { |
| "role": "user", |
| "content": columns["inputs"].strip(), |
| }, |
| { |
| "role": "assistant", |
| "content": columns["targets"].strip(), |
| }, |
| ] |
| |
| return { "text": tokenizer.apply_chat_template(messages, tokenize=False) } |
| |
| dataset.map(format).select_columns(['text', 'language', 'language_code', 'annotation_type', 'user_id']).to_parquet("train.parquet") |
| ``` |
|
|
