Instructions to use minhtoan/gpt2-vietnamese with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use minhtoan/gpt2-vietnamese with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="minhtoan/gpt2-vietnamese")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("minhtoan/gpt2-vietnamese") model = AutoModelForCausalLM.from_pretrained("minhtoan/gpt2-vietnamese") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use minhtoan/gpt2-vietnamese with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "minhtoan/gpt2-vietnamese" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "minhtoan/gpt2-vietnamese", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/minhtoan/gpt2-vietnamese
- SGLang
How to use minhtoan/gpt2-vietnamese with SGLang:
Install from pip and serve model
# Install SGLang from pip: pip install sglang # Start the SGLang server: python3 -m sglang.launch_server \ --model-path "minhtoan/gpt2-vietnamese" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "minhtoan/gpt2-vietnamese", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker images
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 "minhtoan/gpt2-vietnamese" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "minhtoan/gpt2-vietnamese", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use minhtoan/gpt2-vietnamese with Docker Model Runner:
docker model run hf.co/minhtoan/gpt2-vietnamese
GPT-2
GPT-2, a language pretrained model with a causal language modeling (CLM) goal, is a transformer-based language model. This model was pre-trained and used to generate text on the Vietnamese Wikilingua dataset.
How to use the model
from transformers import GPT2Tokenizer, GPT2LMHeadModel
tokenizer = GPT2Tokenizer.from_pretrained('minhtoan/vietnamese-gpt2-finetune')
model = GPT2LMHeadModel.from_pretrained('minhtoan/vietnamese-gpt2-finetune')
text = "Không phải tất cả các nguyên liệu lành mạnh đều đắt đỏ."
input_ids = tokenizer.encode(text, return_tensors='pt')
max_length = 100
sample_outputs = model.generate(input_ids,pad_token_id=tokenizer.eos_token_id,
do_sample=True,
max_length=max_length,
min_length=max_length,
num_return_sequences=3)
for i, sample_output in enumerate(sample_outputs):
print(">> Generated text {}\n\n{}".format(i+1, tokenizer.decode(sample_output.tolist())))
print('\n---')
Author
Phan Minh Toan
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