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--- |
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license: apache-2.0 |
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dataset_info: |
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features: |
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- name: text |
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dtype: string |
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splits: |
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- name: validation |
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num_bytes: 642375 |
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num_examples: 535 |
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- name: train |
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num_bytes: 15585375 |
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num_examples: 12703 |
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download_size: 7315916 |
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dataset_size: 16227750 |
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configs: |
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- config_name: default |
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data_files: |
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- split: validation |
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path: data/validation-* |
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- split: train |
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path: data/train-* |
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--- |
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# Open Assistant Conversations Dataset Release 2 (OASST2) in Uzbek language |
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This dataset is an Uzbek translated version of [OASST2](https://huggingface.co./datasets/OpenAssistant/oasst2) dataset in a thread format with Llama3 chat template. |
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Refer to this [translated version](https://huggingface.co./datasets/MLDataScientist/oasst2_uzbek) if you need the original tree format. Otherwise, use this thread format for fine-tuning Llama3 models. |
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--- |
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The Uzbek translation was completed in 45 hours using a single T4 GPU and [nllb-200-3.3B](https://huggingface.co./facebook/nllb-200-3.3B) model. |
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Based on nllb metrics, you might want to only filter out records that were not originally in English or Russian since English-Uzbek and Russian-Uzbek have acceptable metrics and translation quality is noticeable better for those pairs based on my short reviews. |
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I am sharing the entire Uzbek translated dataset for future research. |
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The following repo and command was used to do the Uzbek translation. |
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Repo: https://github.com/UnderstandLingBV/LLaMa2lang |
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Command used: |
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```!python3 translate.py nllb --model_size 3.3B uzn_Latn output_uzbek --quant8 --base_dataset OpenAssistant/oasst2 --max_length 512 --checkpoint_n 400 --batch_size 40``` |
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I will fine-tune LLAMA3 8B Uzbek chat model and release in HF soon. |
