Instructions to use indobenchmark/indogpt with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use indobenchmark/indogpt with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="indobenchmark/indogpt")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("indobenchmark/indogpt") model = AutoModelForCausalLM.from_pretrained("indobenchmark/indogpt") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use indobenchmark/indogpt with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "indobenchmark/indogpt" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "indobenchmark/indogpt", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/indobenchmark/indogpt
- SGLang
How to use indobenchmark/indogpt 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 "indobenchmark/indogpt" \ --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": "indobenchmark/indogpt", "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 "indobenchmark/indogpt" \ --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": "indobenchmark/indogpt", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use indobenchmark/indogpt with Docker Model Runner:
docker model run hf.co/indobenchmark/indogpt
Tokenizer class IndoNLGTokenizer does not exist or is not currently imported.
I want to try and use this model for my research but i can't load the tokenizer its just appear error that say :
Tokenizer class IndoNLGTokenizer does not exist or is not currently imported.
i ask someone in github and they say :
You should try to ask the other of the model on the community tab how to use it
Hi @Maki21 ,
To use the tokenizer you can use the indobenchmark-toolkit pip package. We couldn't load it with the standard tokenizer since, back then, we make some modification to the tokenization code. You can check how we use the tokenizer on the examples folder of the indonlg repo.
Basically, you can initialize the tokenizer in this way:
from indobenchmark import IndoNLGTokenizer
tokenizer = IndoNLGTokenizer.from_pretrained('indobenchmark/indobart-v2')
Hope it helps!