Text Generation
Transformers
PyTorch
sql
code
gpt_bigcode
SQL generation
Text-to-SQL
text2sql
text-generation-inference
Instructions to use seeklhy/codes-7b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use seeklhy/codes-7b with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="seeklhy/codes-7b")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("seeklhy/codes-7b") model = AutoModelForCausalLM.from_pretrained("seeklhy/codes-7b") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use seeklhy/codes-7b with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "seeklhy/codes-7b" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "seeklhy/codes-7b", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/seeklhy/codes-7b
- SGLang
How to use seeklhy/codes-7b 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 "seeklhy/codes-7b" \ --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": "seeklhy/codes-7b", "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 "seeklhy/codes-7b" \ --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": "seeklhy/codes-7b", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use seeklhy/codes-7b with Docker Model Runner:
docker model run hf.co/seeklhy/codes-7b
| language: | |
| - sql | |
| - code | |
| tags: | |
| - SQL generation | |
| - Text-to-SQL | |
| - text2sql | |
| license: "apache-2.0" | |
| # CodeS-7B | |
| CodeS is a series of Code LLMs specifically optimized for SQL generation. | |
| The CodeS encompasses 1B, 3B, 7B, and 15B scales. CodeS-1B, 3B, and 7B are incrementally pre-trained on the top of StarCoderBase-1B, 3B, and 7B and support the max length of 8,192. Meanwhile, CodeS-15B, derived from StarCoder-15B, accommodates sequences of up to 6,144 tokens. | |
| We have demonstrated that CodeS achieves new state-of-the-art performance on two challenging Text-to-SQL benchmarks: Spider and Bird. | |
| For more details about how to use CodeS, please refer to our GitHub page: https://github.com/RUCKBReasoning/codes. | |
| (This is the repository of CodeS-7B.) | |