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defog
/
sqlcoder

Text Generation
Transformers
PyTorch
English
gpt_bigcode
code
text-generation-inference
Model card Files Files and versions
xet
Community
21

Instructions to use defog/sqlcoder with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use defog/sqlcoder with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("text-generation", model="defog/sqlcoder")
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForCausalLM
    
    tokenizer = AutoTokenizer.from_pretrained("defog/sqlcoder")
    model = AutoModelForCausalLM.from_pretrained("defog/sqlcoder")
  • Notebooks
  • Google Colab
  • Kaggle
  • Local Apps
  • vLLM

    How to use defog/sqlcoder with vLLM:

    Install from pip and serve model
    # Install vLLM from pip:
    pip install vllm
    # Start the vLLM server:
    vllm serve "defog/sqlcoder"
    # Call the server using curl (OpenAI-compatible API):
    curl -X POST "http://localhost:8000/v1/completions" \
    	-H "Content-Type: application/json" \
    	--data '{
    		"model": "defog/sqlcoder",
    		"prompt": "Once upon a time,",
    		"max_tokens": 512,
    		"temperature": 0.5
    	}'
    Use Docker
    docker model run hf.co/defog/sqlcoder
  • SGLang

    How to use defog/sqlcoder 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 "defog/sqlcoder" \
        --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": "defog/sqlcoder",
    		"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 "defog/sqlcoder" \
            --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": "defog/sqlcoder",
    		"prompt": "Once upon a time,",
    		"max_tokens": 512,
    		"temperature": 0.5
    	}'
  • Docker Model Runner

    How to use defog/sqlcoder with Docker Model Runner:

    docker model run hf.co/defog/sqlcoder
New discussion
Resources
  • PR & discussions documentation
  • Code of Conduct
  • Hub documentation

mysql support

1
#19 opened about 2 years ago by
faizelk

Adding `safetensors` variant of this model

#18 opened about 2 years ago by
SFconvertbot

Add more precise license metadata (UI will be cleaner!)

1
#16 opened over 2 years ago by
ashish-soni08

It is possible to run this model on windows with load_in_4bit=True

4
#15 opened over 2 years ago by
JeisonJimenez

Adding `safetensors` variant of this model

#12 opened over 2 years ago by
arkii02

train data or method share

πŸ‘ 3
#10 opened over 2 years ago by
NovasCN

[AUTOMATED] Model Memory Requirements

#8 opened over 2 years ago by
model-sizer-bot

How do I train based on this model?

#6 opened over 2 years ago by
qianmuuq

Will the datasets used for fine-tuning be open-sourced later?

🀝 2
#5 opened over 2 years ago by
leoyangsw

Can more individuals contribute to this

πŸ‘ 1
4
#4 opened over 2 years ago by
desik98

schema consideration and warnings

πŸ‘ 2
5
#3 opened over 2 years ago by
nobitha

Interesting but needs more work?

πŸ‘ 1
1
#2 opened over 2 years ago by
pranjal-codefire

Difficult prompt you may want to add to training data

πŸ‘ 1
1
#1 opened over 2 years ago by
tordbb
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