Instructions to use ajaypanigrahi1997/sqlcoder-7b-finetuned with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use ajaypanigrahi1997/sqlcoder-7b-finetuned with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("defog/sqlcoder-7b-2") model = PeftModel.from_pretrained(base_model, "ajaypanigrahi1997/sqlcoder-7b-finetuned") - Transformers
How to use ajaypanigrahi1997/sqlcoder-7b-finetuned with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="ajaypanigrahi1997/sqlcoder-7b-finetuned")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("ajaypanigrahi1997/sqlcoder-7b-finetuned", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use ajaypanigrahi1997/sqlcoder-7b-finetuned with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "ajaypanigrahi1997/sqlcoder-7b-finetuned" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "ajaypanigrahi1997/sqlcoder-7b-finetuned", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/ajaypanigrahi1997/sqlcoder-7b-finetuned
- SGLang
How to use ajaypanigrahi1997/sqlcoder-7b-finetuned 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 "ajaypanigrahi1997/sqlcoder-7b-finetuned" \ --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": "ajaypanigrahi1997/sqlcoder-7b-finetuned", "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 "ajaypanigrahi1997/sqlcoder-7b-finetuned" \ --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": "ajaypanigrahi1997/sqlcoder-7b-finetuned", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use ajaypanigrahi1997/sqlcoder-7b-finetuned with Docker Model Runner:
docker model run hf.co/ajaypanigrahi1997/sqlcoder-7b-finetuned
Update adapter_config.json
Browse files- adapter_config.json +0 -1
adapter_config.json
CHANGED
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"auto_mapping": null,
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"base_model_name_or_path": "defog/sqlcoder-7b-2",
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"bias": "none",
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"eva_config": null,
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"exclude_modules": null,
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"fan_in_fan_out": false,
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"inference_mode": true,
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"auto_mapping": null,
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"base_model_name_or_path": "defog/sqlcoder-7b-2",
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"bias": "none",
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"exclude_modules": null,
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"fan_in_fan_out": false,
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"inference_mode": true,
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