Instructions to use thangved/text2sql with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use thangved/text2sql with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="thangved/text2sql")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("thangved/text2sql") model = AutoModelForSeq2SeqLM.from_pretrained("thangved/text2sql") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use thangved/text2sql with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "thangved/text2sql" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "thangved/text2sql", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/thangved/text2sql
- SGLang
How to use thangved/text2sql 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 "thangved/text2sql" \ --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": "thangved/text2sql", "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 "thangved/text2sql" \ --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": "thangved/text2sql", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use thangved/text2sql with Docker Model Runner:
docker model run hf.co/thangved/text2sql
| license: apache-2.0 | |
| datasets: | |
| - b-mc2/sql-create-context | |
| - Clinton/Text-to-sql-v1 | |
| language: | |
| - en | |
| metrics: | |
| - bleu | |
| library_name: transformers | |
| pipeline_tag: text2text-generation | |
| tags: | |
| - text-generation-inference | |
| ## Bitex | |
| ```bib | |
| @misc {kim_minh_thang_2023, | |
| author = { {Kim Minh Thang} }, | |
| title = { text2sql (Revision c5cf6ff) }, | |
| year = 2023, | |
| url = { https://huggingface.co/thangved/text2sql }, | |
| doi = { 10.57967/hf/1353 }, | |
| publisher = { Hugging Face } | |
| } | |
| ``` |