| --- |
| license: apache-2.0 |
| dataset_info: |
| features: |
| - name: text |
| dtype: string |
| splits: |
| - name: validation |
| num_bytes: 642375 |
| num_examples: 535 |
| - name: train |
| num_bytes: 15585375 |
| num_examples: 12703 |
| download_size: 7315916 |
| dataset_size: 16227750 |
| configs: |
| - config_name: default |
| data_files: |
| - split: validation |
| path: data/validation-* |
| - split: train |
| path: data/train-* |
| --- |
| |
| # Open Assistant Conversations Dataset Release 2 (OASST2) in Uzbek language |
|
|
| This dataset is an Uzbek translated version of [OASST2](https://huggingface.co/datasets/OpenAssistant/oasst2) dataset in a thread format with Llama3 chat template. |
|
|
| 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. |
|
|
| --- |
|
|
| 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. |
|
|
| The following repo and command was used to do the Uzbek translation. |
|
|
| Repo: https://github.com/UnderstandLingBV/LLaMa2lang |
|
|
| Command used: |
|
|
| ```!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``` |
|
|
| I will fine-tune LLAMA3 8B Uzbek chat model and release in HF soon. |
