Instructions to use Shrishml/starSQL with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Shrishml/starSQL with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="Shrishml/starSQL")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("Shrishml/starSQL") model = AutoModelForCausalLM.from_pretrained("Shrishml/starSQL", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use Shrishml/starSQL with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "Shrishml/starSQL" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Shrishml/starSQL", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/Shrishml/starSQL
- SGLang
How to use Shrishml/starSQL 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 "Shrishml/starSQL" \ --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": "Shrishml/starSQL", "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 "Shrishml/starSQL" \ --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": "Shrishml/starSQL", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use Shrishml/starSQL with Docker Model Runner:
docker model run hf.co/Shrishml/starSQL
Download pytorch_model-00003-of-00004.bin from Shrishml/starSQL: direct link, hf CLI and curl.
- Browser
- Download file 9.86 GB
-
https://huggingface.co/Shrishml/starSQL/resolve/main/pytorch_model-00003-of-00004.bin
- Command line
-
hf download hf://Shrishml/starSQL/pytorch_model-00003-of-00004.bin
-
curl -L -o pytorch_model-00003-of-00004.bin https://huggingface.co/Shrishml/starSQL/resolve/main/pytorch_model-00003-of-00004.bin
9.86 GB
- Xet hash:
- 501fb4d32835b6cb0f28709fa91d88fc224b04c301ea754eebe4f2c8a93545b6
- Size of remote file:
- 9.86 GB
- SHA256:
- 83d6cad84b7dcafec284db6c8e9bf3127dde8816b86046f6715833ed2d7c4448
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