Text Generation
Transformers
Safetensors
Dutch
phi
trl
fietje
alignment-handbook
text-generation-inference
Instructions to use BramVanroy/fietje-2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use BramVanroy/fietje-2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="BramVanroy/fietje-2")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("BramVanroy/fietje-2") model = AutoModelForCausalLM.from_pretrained("BramVanroy/fietje-2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use BramVanroy/fietje-2 with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "BramVanroy/fietje-2" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "BramVanroy/fietje-2", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/BramVanroy/fietje-2
- SGLang
How to use BramVanroy/fietje-2 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 "BramVanroy/fietje-2" \ --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": "BramVanroy/fietje-2", "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 "BramVanroy/fietje-2" \ --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": "BramVanroy/fietje-2", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use BramVanroy/fietje-2 with Docker Model Runner:
docker model run hf.co/BramVanroy/fietje-2
Download training_args.bin from BramVanroy/fietje-2: direct link, hf CLI and curl.
- Browser
- Download file 6.2 kB
-
https://huggingface.co/BramVanroy/fietje-2/resolve/main/training_args.bin
- Command line
-
hf download hf://BramVanroy/fietje-2/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/BramVanroy/fietje-2/resolve/main/training_args.bin
6.2 kB
- Xet hash:
- 79f82d1e727516b31ad0338b7a14c07ee3a947b2f75ad5cb81b3d41c6d5667c3
- Size of remote file:
- 6.2 kB
- SHA256:
- b3c1d5977dd5240895c24187ee76c58266b93791aef53f768847abdb6a7cfbdb
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