Text Generation
Transformers
PyTorch
JAX
TensorBoard
Safetensors
Dutch
gpt2
gpt2-large
text-generation-inference
Instructions to use yhavinga/gpt2-large-dutch with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use yhavinga/gpt2-large-dutch with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="yhavinga/gpt2-large-dutch")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("yhavinga/gpt2-large-dutch") model = AutoModelForCausalLM.from_pretrained("yhavinga/gpt2-large-dutch", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use yhavinga/gpt2-large-dutch with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "yhavinga/gpt2-large-dutch" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "yhavinga/gpt2-large-dutch", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/yhavinga/gpt2-large-dutch
- SGLang
How to use yhavinga/gpt2-large-dutch 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 "yhavinga/gpt2-large-dutch" \ --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": "yhavinga/gpt2-large-dutch", "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 "yhavinga/gpt2-large-dutch" \ --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": "yhavinga/gpt2-large-dutch", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use yhavinga/gpt2-large-dutch with Docker Model Runner:
docker model run hf.co/yhavinga/gpt2-large-dutch
| source ~/venv/bin/activate | |
| while true | |
| do | |
| echo -n "Checking at .. " | |
| date | |
| UPDATED=`git status | grep flax_model | grep modified` | |
| if [ ! -z "$UPDATED" ] | |
| then | |
| sleep 120 | |
| FILE=$(find . -name `ls -tR runs | grep events | head -n 1` | tail -n 1) | |
| STEP=`tensorboard --load_fast=true --inspect --event_file=$FILE | grep last_step | awk '{print $2}'` | |
| git add runs | |
| git add flax_model.msgpack | |
| git commit -m "Saving weights and logs step $STEP" | |
| fi | |
| sleep 60 | |
| done | |