File size: 1,718 Bytes
4b8802f |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 |
---
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.
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. |