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--- |
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license: gemma |
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tags: |
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- unsloth |
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datasets: |
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- Phonepadith/laos-long-content |
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language: |
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- lo |
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metrics: |
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- bleu |
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base_model: |
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- google/gemma-3-12b-it |
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new_version: Phonepadith/aidc-llm-laos-10k-gemma-3-12b-it |
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pipeline_tag: text-generation |
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library_name: fastai |
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--- |
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--- |
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# 🧠 Lao Summarization Model ສົນທະນາ - ສະຫລຸບເນື້ອຫາສຳລັບພາສາລາວ - Fine-tuned Gemma 3 12B IT (10,000 Pairs, Laos Content Input-Output) |
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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-3-12b-it`](https://huggingface.co/google/gemma-3-12b-it). The model is designed to generate concise summaries from Lao language text. |
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**Scope**: |
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- 📚 ສະຫລຸບຂ່າວ |
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- 📚 ສະຫລຸບເອກະສານພາກລັດ |
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- 📚 ສະຫລຸບກອງປະຊຸມ |
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--- |
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# 🧠 Lao AIDC-10K Fine-tuned Gemma-3-12B-IT-V2 |
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**Model ID**: `Phonepadith/aidc-llm-laos-10k-gemma-3-12b-it-v2` |
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**Base Model**: [`google/gemma-3b-it`](https://huggingface.co/google/gemma-3b-it) |
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**Fine-tuned By**: [Phonepadith Phoummavong](https://huggingface.co/Phonepadith) |
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--- |
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## 📌 Model Description |
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This model is a fine-tuned version of **Gemma-3-12B-IT-**, specifically adapted to understand and generate responses in **Lao language** 🇱🇦. It was trained using a curated dataset of over **5,000 high-quality Lao input-output pairs**, primarily focused on **AIDC (Artificial Intelligence and Digital Content)** topics. |
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**Key Features:** |
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- 🗣️ Fine-tuned for Lao language generation |
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- 📚 Suitable for summarization, question answering, general chat |
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- 🧠 Based on Google's powerful Gemma 3-12B Instruct model |
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--- |
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## 🧾 Training Details |
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| Detail | Value | |
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|----------------------|-----------------------------------| |
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| Base Model | Gemma 3-12B Instruct | |
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| Fine-tuning Method | LoRA with PEFT (Unsloth) | |
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| Dataset | 10,000 Laos supervised samples | |
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| Sequence Length | 2048 | |
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| Batch Size | 2 (with gradient accumulation) | |
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| Optimizer | AdamW | |
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| Epochs | 3–5 (early stopping enabled) | |
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| Format | GGUF (F16, Q8_0, Q4_0 available) | |
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--- |
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## 📥 How to Use (LM Studio) |
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1. **Install LM Studio**: [https://lmstudio.ai](https://lmstudio.ai) |
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2. **Import the Model**: |
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- Via Hugging Face: Search for `Phonepadith/aidc-llm-laos-10k-gemma-3-12b-it` |
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- Or drag the `.gguf` file into LM Studio |
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3. **Set System Prompt**: |
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## 📌 Model Details |
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- **Base Model**: [`google/gemma-3-12b-it`](https://huggingface.co/google/gemma-3-12b-it) |
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- **Fine-tuned by**: [Phonepadith](https://huggingface.co/Phonepadith) |
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- **Language**: Lao (`lo`) |
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- **Task**: Text Generation |
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- **Library**: `adapter-transformers` |
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- **License**: Apache 2.0 |
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--- |
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## 📊 Metrics |
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- **Evaluation Metric**: BLEU score |
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BLEU is used to evaluate the quality of generated summaries against reference summaries in the dataset. |
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--- |
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## 🛠️ How to Use |
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You can load and use the model with Hugging Face Transformers and `adapter-transformers`: |
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```python |
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from transformers import AutoTokenizer, AutoModelForCausalLM |
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model_id = "Phonepadith/aidc-llm-laos-10k-gemma-3-12b-it-v2" # change to your actual model name |
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tokenizer = AutoTokenizer.from_pretrained(model_id) |
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model = AutoModelForCausalLM.from_pretrained(model_id) |
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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" |
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inputs = tokenizer(input_text, return_tensors="pt") |
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summary_ids = model.generate(**inputs, max_new_tokens=100) |
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summary = tokenizer.decode(summary_ids[0], skip_special_tokens=True) |
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print(summary) |
