Text Generation
Transformers
Safetensors
English
plbart
code-generation
vulnerability-injection
security
vaitp
finetuned
Instructions to use FBogaerts/plbart-multi_task-python-Finetuned with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use FBogaerts/plbart-multi_task-python-Finetuned with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="FBogaerts/plbart-multi_task-python-Finetuned")# Load model directly from transformers import AutoTokenizer, AutoModelForMultimodalLM tokenizer = AutoTokenizer.from_pretrained("FBogaerts/plbart-multi_task-python-Finetuned") model = AutoModelForMultimodalLM.from_pretrained("FBogaerts/plbart-multi_task-python-Finetuned") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use FBogaerts/plbart-multi_task-python-Finetuned with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "FBogaerts/plbart-multi_task-python-Finetuned" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "FBogaerts/plbart-multi_task-python-Finetuned", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/FBogaerts/plbart-multi_task-python-Finetuned
- SGLang
How to use FBogaerts/plbart-multi_task-python-Finetuned 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 "FBogaerts/plbart-multi_task-python-Finetuned" \ --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": "FBogaerts/plbart-multi_task-python-Finetuned", "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 "FBogaerts/plbart-multi_task-python-Finetuned" \ --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": "FBogaerts/plbart-multi_task-python-Finetuned", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use FBogaerts/plbart-multi_task-python-Finetuned with Docker Model Runner:
docker model run hf.co/FBogaerts/plbart-multi_task-python-Finetuned
File size: 1,904 Bytes
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"content": "__java__",
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"content": "__python__",
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"content": "__en_XX__",
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"sp_model_kwargs": {},
"src_lang": null,
"tgt_lang": null,
"tokenizer_class": "PLBartTokenizer",
"unk_token": "<unk>"
}
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