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