---
license: apache-2.0
dataset_info:
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  - 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.

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.

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.