https://github.com/pythainlp/khanomtanllm
https://github.com/pythainlp/khanomtanllm
Last synced: 12 months ago
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- Host: GitHub
- URL: https://github.com/pythainlp/khanomtanllm
- Owner: PyThaiNLP
- License: apache-2.0
- Created: 2024-08-31T06:49:30.000Z (over 1 year ago)
- Default Branch: main
- Last Pushed: 2024-09-24T15:15:51.000Z (over 1 year ago)
- Last Synced: 2025-03-26T22:11:14.656Z (about 1 year ago)
- Language: Python
- Homepage: http://pythainlp.org/KhanomTanLLM/
- Size: 19.5 KB
- Stars: 15
- Watchers: 1
- Forks: 3
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# KhanomTanLLM
> KhanomTan (Thai name is ขนมตาล) + LLM
> Image gen from [FLUX.1 [dev]](https://huggingface.co/spaces/black-forest-labs/FLUX.1-dev)
KhanomTan LLM is a bilingual language model trained in Thai and English from open source dataset by PyThaiNLP. We train the model from public dataset only. It is a fully open source model. We releses the dataset, training pipeline, and models.
Codename: numfa-v2
Blog Post (Thai): [https://pythainlp.org/2024-09-12-khanomtanllm/](https://pythainlp.org/2024-09-12-khanomtanllm/)
- **Online Demo**: [https://huggingface.co/spaces/wannaphong/KhanomTanLLM-demo](https://huggingface.co/spaces/wannaphong/KhanomTanLLM-demo)
- Pretraining dataset: [https://huggingface.co/datasets/wannaphong/KhanomTanLLM-pretrained-dataset](https://huggingface.co/datasets/wannaphong/KhanomTanLLM-pretrained-dataset)
* Thai subset only: [https://huggingface.co/datasets/wannaphong/KhanomTanLLM-pretrained-dataset-thai-subset](https://huggingface.co/datasets/wannaphong/KhanomTanLLM-pretrained-dataset-thai-subset)
* List Thai subset: [https://huggingface.co/collections/pythainlp/datasets-for-pretrained-thai-llm-65db96ab730386b492889a98](https://huggingface.co/collections/pythainlp/datasets-for-pretrained-thai-llm-65db96ab730386b492889a98)
- Pretraining script: [https://github.com/wannaphong/EasyLM/tree/KhanomTanLLM-pretraining](https://github.com/wannaphong/EasyLM/tree/KhanomTanLLM-pretraining)
- Pretrained Models:
* 1B: [https://huggingface.co/pythainlp/KhanomTanLLM-1B](https://huggingface.co/pythainlp/KhanomTanLLM-1B)
* 3B: [https://huggingface.co/pythainlp/KhanomTanLLM-3B](https://huggingface.co/pythainlp/KhanomTanLLM-3B)
- Instruct Models:
* Instruct dataset: [wannaphong/KhanomTanLLM-Instruct-dataset](https://huggingface.co/datasets/wannaphong/KhanomTanLLM-Instruct-dataset)
* SFT Script: [https://github.com/PyThaiNLP/KhanomTanLLM/tree/main/finetuning](https://github.com/PyThaiNLP/KhanomTanLLM/tree/main/finetuning)
* 1B: [https://huggingface.co/pythainlp/KhanomTanLLM-1B-Instruct](https://huggingface.co/pythainlp/KhanomTanLLM-1B-Instruct)
* 3B: [https://huggingface.co/pythainlp/KhanomTanLLM-3B-Instruct/](https://huggingface.co/pythainlp/KhanomTanLLM-3B-Instruct/)
### Instruct Models
We fine-turning model from [wannaphong/KhanomTanLLM-Instruct-dataset](https://huggingface.co/datasets/wannaphong/KhanomTanLLM-Instruct-dataset). We doesn't have any safeguard, so use your risk.
To get the best result, we suggest the setting:
- temperature: 2 - 4
- min_p: > 0.6
## Acknowledgements
Research supported with Cloud TPUs from Google's [TPU Research Cloud](https://sites.research.google/trc/about/) (TRC). We use TPU4-64 for training model.
Thank you [TPU Research Cloud](https://sites.research.google/trc/about/) and [EasyLM project](https://github.com/young-geng/EasyLM)! We use EasyLM for pretraining model.