Text Generation
Transformers
Safetensors
gemma
text-generation-inference
4-bit precision
bitsandbytes
Instructions to use lbruderer/text-to-sql with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use lbruderer/text-to-sql with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="lbruderer/text-to-sql")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("lbruderer/text-to-sql") model = AutoModelForCausalLM.from_pretrained("lbruderer/text-to-sql") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use lbruderer/text-to-sql with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "lbruderer/text-to-sql" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "lbruderer/text-to-sql", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/lbruderer/text-to-sql
- SGLang
How to use lbruderer/text-to-sql 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 "lbruderer/text-to-sql" \ --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": "lbruderer/text-to-sql", "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 "lbruderer/text-to-sql" \ --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": "lbruderer/text-to-sql", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use lbruderer/text-to-sql with Docker Model Runner:
docker model run hf.co/lbruderer/text-to-sql
- Xet hash:
- 49a25d7ba4e8709935ee174197c5f0a5ad4d8457b905e954fde177afa00d5261
- Size of remote file:
- 2.16 GB
- SHA256:
- 9e0ada619910eb4c4508d0976d604741c805b0f774a65802951c1bf4f4ed9930
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