12 Downloads Updated 6 days ago
ollama run iapp/openthai-1.5-7b:q4_K_M
Updated 6 days ago
6 days ago
38e3a01982fb · 4.7GB

ollama run iapp/openthai-1.5-7b
Official GGUF quantizations of openthaigpt/openthaigpt1.5-7b-instruct
The smallest OpenThai model and the easiest place to start — a 7B Thai chat model that runs on a laptop. Fine-tuned on over 2,000,000 Thai instruction pairs, with multi-turn conversation, RAG and tool-calling support.
If you want reasoning, use R1 32B. If you want Thai law, use OpenThai 2.0 Legal.
| File | Quant | Size | Notes |
|---|---|---|---|
openthaigpt1.5-7b-instruct.Q4_K_M.gguf |
Q4_K_M | ~4.7 GB | Recommended. Runs on 8 GB of RAM or a small GPU. |
openthaigpt1.5-7b-instruct.Q5_K_M.gguf |
Q5_K_M | ~5.4 GB | Better quality, still laptop-friendly. |
openthaigpt1.5-7b-instruct.Q8_0.gguf |
Q8_0 | ~8.1 GB | Near-lossless. |
Ollama
ollama run hf.co/openthaigpt/openthaigpt1.5-7b-instruct-GGUF:Q4_K_M
llama.cpp
llama-cli -m openthaigpt1.5-7b-instruct.Q4_K_M.gguf \
-p "ช่วยสรุปข้อดีข้อเสียของรถยนต์ไฟฟ้าในบริบทประเทศไทย" -n 2048 --temp 0.7
This model uses the ChatML template (<|im_start|> / <|im_end|>), embedded in the
GGUF. Recommended sampling: temperature=0.7, top_p=0.9.
At 7B this is the least capable model in the family — it trades accuracy for the ability to run anywhere. For anything where correctness matters more than convenience, use a larger model. Not safety-tuned for open consumer deployment without your own guardrails.
@misc{yuenyong2024openthaigpt15thaicentric,
title={OpenThaiGPT 1.5: A Thai-Centric Open Source Large Language Model},
author={Sumeth Yuenyong and Kobkrit Viriyayudhakorn and Apivadee Piyatumrong and Jillaphat Jaroenkantasima},
year={2024},
eprint={2411.07238},
archivePrefix={arXiv},
primaryClass={cs.CL},
url={https://arxiv.org/abs/2411.07238}
}
OpenThai (formerly OpenThaiGPT) — free, open-weight Thai large language models from AIEAT and iApp Technology. With thanks to the community members who published unofficial GGUF conversions before these existed.