benchang1110/ChatTaiwan
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How to use benchang1110/SmolLM-135M-Taiwan-Instruct-v1.0 with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("text-generation", model="benchang1110/SmolLM-135M-Taiwan-Instruct-v1.0")
messages = [
{"role": "user", "content": "Who are you?"},
]
pipe(messages) # pip install -U transformers accelerate
# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM
tokenizer = AutoTokenizer.from_pretrained("benchang1110/SmolLM-135M-Taiwan-Instruct-v1.0")
model = AutoModelForCausalLM.from_pretrained("benchang1110/SmolLM-135M-Taiwan-Instruct-v1.0", device_map="auto")
messages = [
{"role": "user", "content": "Who are you?"},
]
inputs = tokenizer.apply_chat_template(
messages,
add_generation_prompt=True,
tokenize=True,
return_dict=True,
return_tensors="pt",
).to(model.device)
outputs = model.generate(**inputs, max_new_tokens=256)
print(tokenizer.decode(outputs[0][inputs["input_ids"].shape[-1]:]))How to use benchang1110/SmolLM-135M-Taiwan-Instruct-v1.0 with vLLM:
# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "benchang1110/SmolLM-135M-Taiwan-Instruct-v1.0"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
-H "Content-Type: application/json" \
--data '{
"model": "benchang1110/SmolLM-135M-Taiwan-Instruct-v1.0",
"messages": [
{
"role": "user",
"content": "What is the capital of France?"
}
]
}'docker model run hf.co/benchang1110/SmolLM-135M-Taiwan-Instruct-v1.0
How to use benchang1110/SmolLM-135M-Taiwan-Instruct-v1.0 with SGLang:
# Install SGLang from pip:
pip install sglang
# Start the SGLang server:
python3 -m sglang.launch_server \
--model-path "benchang1110/SmolLM-135M-Taiwan-Instruct-v1.0" \
--host 0.0.0.0 \
--port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
-H "Content-Type: application/json" \
--data '{
"model": "benchang1110/SmolLM-135M-Taiwan-Instruct-v1.0",
"messages": [
{
"role": "user",
"content": "What is the capital of France?"
}
]
}'docker run --gpus all \
--shm-size 32g \
-p 30000:30000 \
-v ~/.cache/huggingface:/root/.cache/huggingface \
--env "HF_TOKEN=<secret>" \
--ipc=host \
lmsysorg/sglang:latest \
python3 -m sglang.launch_server \
--model-path "benchang1110/SmolLM-135M-Taiwan-Instruct-v1.0" \
--host 0.0.0.0 \
--port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
-H "Content-Type: application/json" \
--data '{
"model": "benchang1110/SmolLM-135M-Taiwan-Instruct-v1.0",
"messages": [
{
"role": "user",
"content": "What is the capital of France?"
}
]
}'How to use benchang1110/SmolLM-135M-Taiwan-Instruct-v1.0 with Docker Model Runner:
docker model run hf.co/benchang1110/SmolLM-135M-Taiwan-Instruct-v1.0
This model is the instruction finetuning version of benchang1110/SmolLM-135M-Taiwan.
import torch, transformers
def generate_response():
model = transformers.AutoModelForCausalLM.from_pretrained("benchang1110/SmolLM-135M-Taiwan-Instruct-v1.0").to(device)
tokenizer = transformers.AutoTokenizer.from_pretrained("benchang1110/SmolLM-135M-Taiwan-Instruct-v1.0")
streamer = transformers.TextStreamer(tokenizer,skip_prompt=True)
while(1):
prompt = input('USER:')
if prompt == "exit":
break
print("Assistant: ")
message = [
{'content': prompt, 'role': 'user'},
]
formatted_chat = tokenizer.apply_chat_template(message,tokenize=True,add_generation_prompt=True,return_tensors='pt').to(device)
_ = model.generate(formatted_chat,streamer=streamer,use_cache=True,max_new_tokens=1024,do_sample=True)
if __name__ == '__main__':
device = 'cuda' if torch.cuda.is_available() else 'cpu'
generate_response()
<|im_start|>user
寫一首詩<|im_end|>
<|im_start|>assistant
在廣袤的夜色中,我漫步在思緒裡,
月光灑落在我身上的角落,
思緒如龍舞,隨著微風而逝,
我是島嶼的一部分,美麗又哀愁。
我思念海,思念故鄉,
朝陽灑落在草地上的粼粼,
海鷗在腳下跳舞,鳥兒在樹梢跳躍,
這是我的故鄉氣息,永恆的頌歌。
我曾許下希望,也曾動靜,
為的只是與自然為伍,為的只是與世隔絕,
即使身處千里之外,我的心,始終相連。
我與海洋共舞,與天空共鳴,
我與山巒疊於石縫,與樹木相互依存,
我是台灣,一顆愛的蝴蝶,
展翅飛翔,追求著夢的開始。
我思念台北城,千奇百怪的夜市,
我思念台灣人,溫暖的笑容,溫馨的家庭,
我思念客家花市,田園風光如畫,
我思念台灣,像一首動人的歌,
我在我的土地上,找到歸屬。
無論時光流逝,我將永遠熱愛這片土地,
我將用餘生,去提醒世人,關於台灣,
關於它的美,關於它的魅力,
因為它是我,我心之所在。
我是台灣,美麗而多元的一部分,
我驕傲地稱你為家,
你是我心中的旅伴,我愛你,
台灣,我愛你,
我將永遠熱愛你,我的家。<|im_end|>