Text Generation
Transformers
PyTorch
JAX
TensorBoard
Safetensors
Dutch
gpt2
gpt2-medium
text-generation-inference
Instructions to use yhavinga/gpt2-medium-dutch with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use yhavinga/gpt2-medium-dutch with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="yhavinga/gpt2-medium-dutch")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("yhavinga/gpt2-medium-dutch") model = AutoModelForCausalLM.from_pretrained("yhavinga/gpt2-medium-dutch") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use yhavinga/gpt2-medium-dutch with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "yhavinga/gpt2-medium-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-medium-dutch", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/yhavinga/gpt2-medium-dutch
- SGLang
How to use yhavinga/gpt2-medium-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-medium-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-medium-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-medium-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-medium-dutch", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use yhavinga/gpt2-medium-dutch with Docker Model Runner:
docker model run hf.co/yhavinga/gpt2-medium-dutch
- Xet hash:
- df66e589b63b5651504fbf89482e40d9eb6497162a4b50a4bce2724230a11cdf
- Size of remote file:
- 1.42 GB
- SHA256:
- a5b7d6e0a2d7b5a04dbf348d2196ad0fc3797612d0a846685cea7685fb916543
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.