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---
language:
- th
- en
base_model:
- Qwen/Qwen2.5-7B-Instruct
- Qwen/Qwen2.5-7B
pipeline_tag: text-generation
library_name: transformers
datasets:
- airesearch/WangchanX-Legal-ThaiCCL-RAG
- airesearch/WangchanThaiInstruct
- pythainlp/han-instruct-dataset-v4.0
---
<img src="./Tsunami.webp" alt="Tsunami Model" width="800" style="margin-left:'auto' margin-right:'auto' display:'block'"/>
# Tsunami-0.5-7B-Instruct
**TSUNAMI**: Transformative Semantic Understanding and Natural Augmentation Model for Intelligence.
**TSUNAMI** full name was created by ChatGPT.
---
### infomation
**Tsunami-0.5-7B-Instruct** is Thai Large Language Model that fine-tuned from **Qwen2.5-7B** around **60,000** rows in Thai-specific domain.
---
### 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-0.5-7B-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 | [email protected]
---
- **Tsunami-0.5-7B-Instruct** is the version 0.5 that did not train on the whole dataset.
- **Tsunami-1.0-7B-Instruct** is coming soon. |