tahrirchi
/

dilmash

@@ -1,199 +1,99 @@
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 library_name: transformers
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 ---
 library_name: transformers
 license: cc-by-nc-4.0
+datasets:
+- tahrirchi/dilmash
+tags:
+- nllb
+- karakalpak
+language:
+- en
+- ru
+- uz
+- kaa
+base_model: facebook/nllb-200-distilled-600M
+pipeline_tag: translation
 ---
+# Dilmash: Karakalpak Machine Translation Models
+This repository contains a collection of machine translation models for the Karakalpak language, developed as part of the research paper "Open Language Data Initiative: Advancing Low-Resource Machine Translation for Karakalpak".
+## Model variations
+We provide three variants of our Karakalpak translation model:
+| Model | Base Model | Parameters | Tokenizer Length | Datasets | Languages |
+|-------|------------|------------|-------------------|----------|-----------|
+| [`dilmash-raw`](https://huggingface.co/tahrirchi/dilmash-raw) | [nllb-200-600M](https://huggingface.co/facebook/nllb-200-distilled-600M) | 615M | 256,204 | [Dilmash corpus](https://huggingface.co/datasets/tahrirchi/dilmash) | Karakalpak, Uzbek, Russian, English |
+| **[`dilmash`](https://huggingface.co/tahrirchi/dilmash)** | **[nllb-200-600M](https://huggingface.co/facebook/nllb-200-distilled-600M)** | **629M** | **269,399** | **[Dilmash corpus](https://huggingface.co/datasets/tahrirchi/dilmash)** | **Karakalpak, Uzbek, Russian, English** |
+| [`dilmash-TIL`](https://huggingface.co/tahrirchi/dilmash-TIL) | [nllb-200-600M](https://huggingface.co/facebook/nllb-200-distilled-600M) | 629M | 269,399 | [Dilmash corpus](https://huggingface.co/datasets/tahrirchi/dilmash), TIL corpus | Karakalpak, Uzbek, Russian, English |
+## Intended uses & limitations
+These models are designed for machine translation tasks involving the Karakalpak language. They can be used for translation between Karakalpak, Uzbek, Russian, or English.
+### How to use
+You can use these models with the Transformers library. Here's a quick example:
+```python
+from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
+model_ckpt = "tahrirchi/dilmash"
+tokenizer = AutoTokenizer.from_pretrained(model_ckpt)
+model = AutoModelForSeq2SeqLM.from_pretrained(model_ckpt)
+# Example translation
+input_text = "Here is dilmash translation model."
+tokenizer.src_lang = "eng_Latn"
+tokenizer.tgt_lang = "kaa_Latn"
+inputs = tokenizer(input_text, return_tensors="pt")
+outputs = model.generate(**inputs)
+translated_text = tokenizer.decode(outputs[0], skip_special_tokens=True)
+print(translated_text) # Dilmash awdarması modeli.
+```
+## Training data
+The models were trained on a parallel corpus of 300,000 sentence pairs, including:
+- Uzbek-Karakalpak (100,000 pairs)
+- Russian-Karakalpak (100,000 pairs)
+- English-Karakalpak (100,000 pairs)
+The dataset is available [here](https://huggingface.co/datasets/tahrirchi/dilmash).
+## Training procedure
+For full details of the training procedure, please refer to our paper (coming soon!).
+## Citation
+If you use these models in your research, please cite our paper:
+```bibtex
+@inproceedings{mamasaidov2024advancing,
+  title={Open Language Data Initiative: Advancing Low-Resource Machine Translation for Karakalpak},
+  author={Mamasaidov, Mukhammadsaid and Shopulatov, Abror},
+  booktitle={Proceedings of the OLDI Workshop},
+  year={2024}
+}
+```
+## Gratitude
+We are thankful to these awesome organizations and people for helping to make it happen:
+ - [David Dalé](https://daviddale.ru): for advise throughout the process
+ - Perizad Najimova: for expertise and assistance with the Karakalpak language
+ - [Nurlan Pirjanov](https://www.linkedin.com/in/nurlan-pirjanov/): for expertise and assistance with the Karakalpak language
+ - [Atabek Murtazaev](https://www.linkedin.com/in/atabek/): for advise throughout the process
+ - Ajiniyaz Nurniyazov: for advise throughout the process
+## Contacts
+We believe that this work will enable and inspire all enthusiasts around the world to open the hidden beauty of low-resource languages, in particular Karakalpak.
+For further development and issues about the dataset, please use m.mamasaidov@tahrirchi.uz or a.shopolatov@tahrirchi.uz to contact.