Instructions to use Jnx03/kanitakorn-v14a-v14a-step160 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use Jnx03/kanitakorn-v14a-v14a-step160 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("typhoon-ai/typhoon-s-thaillm-8b-instruct-research-preview") model = PeftModel.from_pretrained(base_model, "Jnx03/kanitakorn-v14a-v14a-step160") - Notebooks
- Google Colab
- Kaggle
| library_name: peft | |
| base_model: typhoon-ai/typhoon-s-thaillm-8b-instruct-research-preview | |
| license: apache-2.0 | |
| tags: | |
| - thai | |
| - kanitakorn | |
| - single-model | |
| - greedy-eval | |
| language: | |
| - th | |
| - en | |
| # Jnx03/kanitakorn-v14a-v14a-step160 | |
| Kanitakorn 2026-06-13 campaign artifact. | |
| - Base: `typhoon-ai/typhoon-s-thaillm-8b-instruct-research-preview` | |
| - Version: `v14a-step160` | |
| - Method: `sft-lora` | |
| - Final-claim policy: one model, no BoN, no self-consistency, no ensemble, no model routing. | |
| - Date: 2026-06-13 | |
| ## Scores | |
| | Benchmark | Score | Target | Status | | |
| |---|---:|---:|---| | |
| | aime24_th | pending | >15.0 | pending | | |
| | aime24 | pending | >25.0 | pending | | |
| | math500_th | pending | >56.0 | pending | | |
| | math500 | pending | >82.0 | pending | | |
| | livecodebench_th | pending | >35.0 | pending | | |
| | livecodebench | pending | >60.0 | pending | | |
| | openthaieval | pending | >80.0 | pending | | |
| | hotpotqa_th_en | pending | >46.0 | pending | | |
| | instruction_following_th_en | pending | >57.0 | pending | | |
| | mt_bench_th_en | pending | >85.0 | pending | | |
| | thaiexam | pending | >70.0 | pending | | |
| | ifeval_th | pending | >82.0 | pending | | |
| ## Notes | |
| Automatic checkpoint publish from runs/20260613_typhoon8b_v14a_harderror_fast_r16_lr5e6_400/checkpoint-160. Single-model artifact; no BoN/self-consistency. | |