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---
language:
- th
- en
license: cc-by-nc-3.0
datasets:
- airesearch/concat_six_dataset_th_en
---
# typhoon-7b-WangchanX-sft-Demo
This model is based on [WangchanX Fine-tuning Pipeline](https://github.com/vistec-AI/WangchanX).
GitHub: [WangchanX Fine-tuning Pipeline](https://github.com/vistec-AI/WangchanX).
Pre-train model from scb10x/typhoon-7b and fine tuning with Qlora.
License: cc-by-nc-3.0
## Train Example
Train WangchanX pipeline: [Colab](https://colab.research.google.com/github/vistec-AI/WangchanX/blob/main/notebooks/Train_WangchanX_pipeline.ipynb)
## Inference Example
Run on [Colab](https://colab.research.google.com/drive/1PeUnv89Ao2uHRYYzZVOlUwoBUdYKFbLS?usp=sharing)
### Prepare your model and tokenizer:
```python
import torch
from transformers import AutoTokenizer, AutoModelForCausalLM
# Model path
path = "airesearch/typhoon-7b-WangchanX-sft-Demo"
# Device
device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')
# Load tokenizer and model
tokenizer = AutoTokenizer.from_pretrained(path, use_fast=False)
model = AutoModelForCausalLM.from_pretrained(path, device_map="auto")
```
### Define chat messages:
```python
messages = [
{"role": "user", "content": "ลิเก กับ งิ้ว ต่างกันอย่างไร"},
]
```
### Tokenize chat messages:
```python
tokenized_chat = tokenizer.apply_chat_template(messages, tokenize=True, add_generation_prompt=True, return_tensors="pt").to(device)
print(tokenizer.decode(tokenized_chat[0]))
```
<details close>
<summary>Output: </summary>
<br>
<pre lang="markdown">
<|user|>
ลิเก กับ งิ้ว ต่างกันอย่างไร</s>
<|assistant|></pre>
</details>
### Generate responses:
```python
outputs = model.generate(tokenized_chat, max_length=2048)
print(tokenizer.decode(outputs[0]))
```
<details close>
<summary>Output: </summary>
<br>
<pre lang="markdown">
<|user|>
ลิเก กับ งิ้ว ต่างกันอย่างไร</s>
<|assistant|>
ต่างกันที่วัฒนธรรมการแสดง ลิเกเป็นละครเพลงของไทย ส่วนงิ้วเป็นการแสดงพื้นบ้านของจีน</s></pre>
</details> |