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RichardErkhov/
Tsunami-th_-_Tsunami-0.5x-7B-Instruct-gguf

Name: Tsunami-th_-_Tsunami-0.5x-7B-Instruct-gguf
Availability: InStock

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Tsunami-0.5x-7B-Instruct - GGUF

Model creator: https://huggingface.co/Tsunami-th/
Original model: https://huggingface.co/Tsunami-th/Tsunami-0.5x-7B-Instruct/

Name	Quant method	Size
Tsunami-0.5x-7B-Instruct.Q2_K.gguf	Q2_K	2.81GB
Tsunami-0.5x-7B-Instruct.Q3_K_S.gguf	Q3_K_S	3.25GB
Tsunami-0.5x-7B-Instruct.Q3_K.gguf	Q3_K	3.55GB
Tsunami-0.5x-7B-Instruct.Q3_K_M.gguf	Q3_K_M	3.55GB
Tsunami-0.5x-7B-Instruct.Q3_K_L.gguf	Q3_K_L	3.81GB
Tsunami-0.5x-7B-Instruct.IQ4_XS.gguf	IQ4_XS	3.96GB
Tsunami-0.5x-7B-Instruct.Q4_0.gguf	Q4_0	4.13GB
Tsunami-0.5x-7B-Instruct.IQ4_NL.gguf	IQ4_NL	4.16GB
Tsunami-0.5x-7B-Instruct.Q4_K_S.gguf	Q4_K_S	4.15GB
Tsunami-0.5x-7B-Instruct.Q4_K.gguf	Q4_K	4.36GB
Tsunami-0.5x-7B-Instruct.Q4_K_M.gguf	Q4_K_M	4.36GB
Tsunami-0.5x-7B-Instruct.Q4_1.gguf	Q4_1	4.54GB
Tsunami-0.5x-7B-Instruct.Q5_0.gguf	Q5_0	4.95GB
Tsunami-0.5x-7B-Instruct.Q5_K_S.gguf	Q5_K_S	4.95GB
Tsunami-0.5x-7B-Instruct.Q5_K.gguf	Q5_K	5.07GB
Tsunami-0.5x-7B-Instruct.Q5_K_M.gguf	Q5_K_M	5.07GB
Tsunami-0.5x-7B-Instruct.Q5_1.gguf	Q5_1	5.36GB
Tsunami-0.5x-7B-Instruct.Q6_K.gguf	Q6_K	5.82GB
Tsunami-0.5x-7B-Instruct.Q8_0.gguf	Q8_0	7.54GB

Original model description:

language:

th
en license: apache-2.0 library_name: transformers base_model:
Qwen/Qwen2.5-7B-Instruct
Qwen/Qwen2.5-7B pipeline_tag: text-generation model-index:
name: Tsunami-0.5x-7B-Instruct results:
- task: type: text-generation name: Text Generation dataset: name: IFEval (0-Shot) type: HuggingFaceH4/ifeval args: num_few_shot: 0 metrics:
  - type: inst_level_strict_acc and prompt_level_strict_acc value: 70.99 name: strict accuracy source: url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Tsunami-th/Tsunami-0.5x-7B-Instruct name: Open LLM Leaderboard
- task: type: text-generation name: Text Generation dataset: name: BBH (3-Shot) type: BBH args: num_few_shot: 3 metrics:
  - type: acc_norm value: 37.36 name: normalized accuracy source: url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Tsunami-th/Tsunami-0.5x-7B-Instruct name: Open LLM Leaderboard
- task: type: text-generation name: Text Generation dataset: name: MATH Lvl 5 (4-Shot) type: hendrycks/competition_math args: num_few_shot: 4 metrics:
  - type: exact_match value: 4.83 name: exact match source: url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Tsunami-th/Tsunami-0.5x-7B-Instruct name: Open LLM Leaderboard
- task: type: text-generation name: Text Generation dataset: name: GPQA (0-shot) type: Idavidrein/gpqa args: num_few_shot: 0 metrics:
  - type: acc_norm value: 8.61 name: acc_norm source: url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Tsunami-th/Tsunami-0.5x-7B-Instruct name: Open LLM Leaderboard
- task: type: text-generation name: Text Generation dataset: name: MuSR (0-shot) type: TAUR-Lab/MuSR args: num_few_shot: 0 metrics:
  - type: acc_norm value: 18.57 name: acc_norm source: url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Tsunami-th/Tsunami-0.5x-7B-Instruct name: Open LLM Leaderboard
- task: type: text-generation name: Text Generation dataset: name: MMLU-PRO (5-shot) type: TIGER-Lab/MMLU-Pro config: main split: test args: num_few_shot: 5 metrics:
  - type: acc value: 38.42 name: accuracy source: url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Tsunami-th/Tsunami-0.5x-7B-Instruct name: Open LLM Leaderboard

Tsunami-0.5x-7B-Instruct

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

TSUNAMI full name was created by ChatGPT.

infomation

Tsunami-0.5x-7B-Instruct is Thai Large Language Model that fine-tuned from Qwen2.5-7B around 100,000 rows in Thai dataset.

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

python

from transformers import AutoModelForCausalLM, AutoTokenizer
import torch

model_name = "Tsunami-th/Tsunami-0.5x-7B-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)

Author

Pollakrit Lorprasertkul | game.pollakrit@gmail.com

Tsunami-0.5x-7B-Instruct is the version 0.5x that did not train on the whole dataset.
Tsunami-1.0-7B-Instruct is coming soon.

Open LLM Leaderboard Evaluation Results

Detailed results can be found here

Metric	Value
Avg.	29.80
IFEval (0-Shot)	70.99
BBH (3-Shot)	37.36
MATH Lvl 5 (4-Shot)	4.83
GPQA (0-shot)	8.61
MuSR (0-shot)	18.57
MMLU-PRO (5-shot)	38.42

RichardErkhov/Tsunami-th_-_Tsunami-0.5x-7B-Instruct-gguf