Tsunami-1.0-14B-Instruct
TSUNAMI: Transformative Semantic Understanding and Natural Augmentation Model for Intelligence.
TSUNAMI full name was created by ChatGPT.
infomation
Tsunami-1.0-14B-Instruct is Thai Large Language Model that fine-tuned from Qwen2.5-14B in Thai dataset.
Author
- Pollakrit Lorprasertkul | game.pollakrit@gmail.com
Performance Evaluation
Below are the benchmark results of Tsunami-1.0-14B-Instruct compared to similar models in its class:
| Model | Average | Thai Exam | M3Exam |
|---|---|---|---|
| Qwen2.5-14B-Instruct | 58.45 | 57.35 | 59.55 |
| Meta-Llama-3.1-70B-Instruct | 59.38 | 58.23 | 60.52 |
| llama-3-typhoon-v1.5x-70b-instruct | 59.34 | 58.76 | 59.92 |
| openthaigpt1.5-14b-instruct | 60.41 | 58.41 | 62.41 |
| Tsunami-1.0-14B-Instruct | 62.05 | 61.06 | 63.05 |
Prompt Template
This model uses ChatML prompt template:
<|im_start|>system
{System}<|im_end|>
<|im_start|>user
{User}<|im_end|>
<|im_start|>assistant
{Assistant}
How to use
from transformers import AutoModelForCausalLM, AutoTokenizer
import torch
model_name = "Tsunami-th/Tsunami-1.0-14B-Instruct"
model = AutoModelForCausalLM.from_pretrained(
model_name,
torch_dtype="auto",
device_map="auto"
)
tokenizer = AutoTokenizer.from_pretrained(model_name)
messages = [
{"role": "system", "content": "You are a helpful assistant."},
{"role": "user", "content": "สวัสดีครับ"}
]
text = tokenizer.apply_chat_template(
messages,
tokenize=False,
add_generation_prompt=True
)
inputs = tokenizer(text, return_tensors="pt")
inputs = inputs.to(model.device)
with torch.no_grad():
output = model.generate(**inputs, max_new_tokens=512)
response = tokenizer.decode(output[0, len(inputs['input_ids'][0]):], skip_special_tokens=True)