README.md

metadata

language:
  - th
  - en
license: apache-2.0
library_name: transformers
base_model:
  - Qwen/Qwen2.5-14B-Instruct
  - Qwen/Qwen2.5-14B
pipeline_tag: text-generation

Tsunami-1.0-14B-Instruct

TSUNAMI: Transformative Semantic Understanding and Natural Augmentation Model for Intelligence.

TSUNAMI full name was created by ChatGPT.

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infomation

Tsunami-1.0-14B-Instruct is Thai Large Language Model that fine-tuned from Qwen2.5-14B in Thai dataset.

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Author

• Pollakrit Lorprasertkul | game.pollakrit@gmail.com

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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

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Prompt Template

This model uses ChatML prompt template:

<|im_start|>system
{System}<|im_end|>
<|im_start|>user
{User}<|im_end|>
<|im_start|>assistant
{Assistant}

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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)

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