Text Generation
Transformers
TensorBoard
Safetensors
mixformer-sequential
Generated from Trainer
custom_code
Instructions to use machinelearningzuu/phi-1_5-finetuned-sql-injection with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use machinelearningzuu/phi-1_5-finetuned-sql-injection with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="machinelearningzuu/phi-1_5-finetuned-sql-injection", trust_remote_code=True)# Load model directly from transformers import AutoModelForCausalLM model = AutoModelForCausalLM.from_pretrained("machinelearningzuu/phi-1_5-finetuned-sql-injection", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use machinelearningzuu/phi-1_5-finetuned-sql-injection with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "machinelearningzuu/phi-1_5-finetuned-sql-injection" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "machinelearningzuu/phi-1_5-finetuned-sql-injection", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/machinelearningzuu/phi-1_5-finetuned-sql-injection
- SGLang
How to use machinelearningzuu/phi-1_5-finetuned-sql-injection 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 "machinelearningzuu/phi-1_5-finetuned-sql-injection" \ --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": "machinelearningzuu/phi-1_5-finetuned-sql-injection", "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 "machinelearningzuu/phi-1_5-finetuned-sql-injection" \ --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": "machinelearningzuu/phi-1_5-finetuned-sql-injection", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use machinelearningzuu/phi-1_5-finetuned-sql-injection with Docker Model Runner:
docker model run hf.co/machinelearningzuu/phi-1_5-finetuned-sql-injection
- Xet hash:
- 3a09a07b3a825845ab7bf13866faeb46c9f0dff8c08267e9922e87a13dc63aa2
- Size of remote file:
- 18.9 MB
- SHA256:
- 79efd2ceac1ff748d180ff8b61ac809485a429ac1e7be0e77cd042f3ae2ba487
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