Text Generation
Transformers
Safetensors
French
fiscalité
génération-de-texte
français
8-bit precision
Instructions to use Aktraiser/modele-test with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Aktraiser/modele-test with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="Aktraiser/modele-test")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Aktraiser/modele-test", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use Aktraiser/modele-test with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "Aktraiser/modele-test" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Aktraiser/modele-test", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/Aktraiser/modele-test
- SGLang
How to use Aktraiser/modele-test 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 "Aktraiser/modele-test" \ --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": "Aktraiser/modele-test", "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 "Aktraiser/modele-test" \ --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": "Aktraiser/modele-test", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use Aktraiser/modele-test with Docker Model Runner:
docker model run hf.co/Aktraiser/modele-test
Update handler.py
Browse files- handler.py +4 -4
handler.py
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@@ -48,10 +48,10 @@ class EndpointHandler:
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**generation_kwargs
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)
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# Formater la sortie
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if isinstance(outputs, list):
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return {"generated_text":
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return {"generated_text": outputs["generated_text"]}
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except Exception as e:
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return {"error": str(e)}
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**generation_kwargs
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)
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+
# Formater la sortie en tableau comme requis par l'API
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if isinstance(outputs, list):
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return [{"generated_text": output["generated_text"]} for output in outputs]
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return [{"generated_text": outputs["generated_text"]}]
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except Exception as e:
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return [{"error": str(e)}]
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