Instructions to use aariciah/gpt2-german-dutch-synsem with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use aariciah/gpt2-german-dutch-synsem with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="aariciah/gpt2-german-dutch-synsem")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("aariciah/gpt2-german-dutch-synsem") model = AutoModelForCausalLM.from_pretrained("aariciah/gpt2-german-dutch-synsem", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use aariciah/gpt2-german-dutch-synsem with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "aariciah/gpt2-german-dutch-synsem" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "aariciah/gpt2-german-dutch-synsem", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/aariciah/gpt2-german-dutch-synsem
- SGLang
How to use aariciah/gpt2-german-dutch-synsem 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 "aariciah/gpt2-german-dutch-synsem" \ --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": "aariciah/gpt2-german-dutch-synsem", "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 "aariciah/gpt2-german-dutch-synsem" \ --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": "aariciah/gpt2-german-dutch-synsem", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use aariciah/gpt2-german-dutch-synsem with Docker Model Runner:
docker model run hf.co/aariciah/gpt2-german-dutch-synsem
Download training_args.bin from aariciah/gpt2-german-dutch-synsem: direct link, hf CLI and curl.
- Browser
- Download file 5.91 kB
-
https://huggingface.co/aariciah/gpt2-german-dutch-synsem/resolve/main/training_args.bin
- Command line
-
hf download hf://aariciah/gpt2-german-dutch-synsem/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/aariciah/gpt2-german-dutch-synsem/resolve/main/training_args.bin
5.91 kB
- Xet hash:
- f4da78393c7bcbd9fff6f44af538c5492a8374ea9152359ba03de8cd9bf92490
- Size of remote file:
- 5.91 kB
- SHA256:
- 9a3d94951a379d9f81e50d9125f177b5b85090719e93c11384e064bf6fbf3e84
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