|
|
--- |
|
|
license: apache-2.0 |
|
|
datasets: |
|
|
- Phonepadith/laos_word_dataset |
|
|
language: |
|
|
- lo |
|
|
metrics: |
|
|
- bleu |
|
|
base_model: |
|
|
- google/gemma-3-4b-it |
|
|
pipeline_tag: summarization |
|
|
library_name: fastai |
|
|
tags: |
|
|
- unsloth |
|
|
--- |
|
|
# 🧠 Lao Summarization Model ສຳລັບສະຫລຸບເນື້ອຫາ - Fine-tuned Gemma 3 4B IT |
|
|
|
|
|
This is a **Lao language summarization model** fine-tuned on the [`Phonepadith/laos_word_dataset`](https://huggingface.co/datasets/Phonepadith/laos_word_dataset), using the base model [`google/gemma-3-4b-it`](https://huggingface.co/google/gemma-3-4b-it). The model is designed to generate concise summaries from Lao language text. |
|
|
|
|
|
--- |
|
|
|
|
|
## 📌 Model Details |
|
|
|
|
|
- **Base Model**: [`google/gemma-3-4b-it`](https://huggingface.co/google/gemma-3-4b-it) |
|
|
- **Fine-tuned by**: [Phonepadith](https://huggingface.co/Phonepadith) |
|
|
- **Language**: Lao (`lo`) |
|
|
- **Task**: Summarization |
|
|
- **Dataset**: [`Phonepadith/laos_word_dataset`](https://huggingface.co/datasets/Phonepadith/laos_word_dataset) |
|
|
- **Library**: `adapter-transformers` |
|
|
- **License**: Apache 2.0 |
|
|
|
|
|
--- |
|
|
|
|
|
## 📊 Metrics |
|
|
|
|
|
- **Evaluation Metric**: BLEU score |
|
|
BLEU is used to evaluate the quality of generated summaries against reference summaries in the dataset. |
|
|
|
|
|
--- |
|
|
|
|
|
## 🛠️ How to Use |
|
|
|
|
|
You can load and use the model with Hugging Face Transformers and `adapter-transformers`: |
|
|
|
|
|
```python |
|
|
|
|
|
from transformers import AutoTokenizer, AutoModelForCausalLM |
|
|
|
|
|
model_id = "Phonepadith/Laollm" # change to your actual model name |
|
|
tokenizer = AutoTokenizer.from_pretrained(model_id) |
|
|
model = AutoModelForCausalLM.from_pretrained(model_id) |
|
|
|
|
|
input_text = "ປັດຈຸບັນ ກອງທັບປະຊາຊົນລາວ ມີການປະກອບວັດຖຸເຕັກນິກທັນສະໄໝສົມຄວນ, ສາມາດຕອບສະໜອງ ໃຫ້ແກ່ວຽກງານປ້ອງກັນຊາດ ໃນໄລຍະໃໝ່ ໄດ້ໂດຍພື້ນຖານ; ໄດ້ປະກອບສ່ວນຢ່າງຕັ້ງໜ້າເຂົ້າໃນການປ້ອງກັນ, ຄວບຄຸມໄພພິບັດ ແລະ ຊ່ວຍເຫລືອປະຊາຊົນ ຜູ້ປະສົບໄພພິບັດທຳມະຊາດຕ່າງໆທີ່ເກີດຂຶ້ນໃນຂອບເຂດທົ່ວປະເທດ. ພ້ອມນັ້ນ, ກໍໄດ້ເປັນເຈົ້າການປະກອບສ່ວນປັບປຸງກໍ່ສ້າງພື້ນ ຖານການເມືອງ, ກໍ່ສ້າງທ່າສະໜາມສົງຄາມປະຊາຊົນ 3 ຂັ້ນ ຕິດພັນກັບວຽກງານ 3 ສ້າງ ຢູ່ທ້ອງຖິ່ນຕາມ 4 ເນື້ອໃນ 4 ຄາດໝາຍ ແລະ ສືບທອດມູນເຊື້ອຄວາມສາມັກຄີ ກັບກອງທັບປະເທດເພື່ອນມິດ ສາກົນ, ປະຕິບັດນະໂຍບາຍເພີ່ມມິດຫລຸດຜ່ອນສັດຕູ, ຮັບປະກັນສະຖຽນລະພາບ ຂອງລະບອບການ ເມືອງ, ຮັກສາຄວາມສະຫງົບປອດໄພຕາມຊາຍແດນ" |
|
|
inputs = tokenizer(input_text, return_tensors="pt") |
|
|
summary_ids = model.generate(**inputs, max_new_tokens=100) |
|
|
summary = tokenizer.decode(summary_ids[0], skip_special_tokens=True) |
|
|
|
|
|
print(summary) |
