Instructions to use LarkAI/codet5p-770m_nl2sql_oig with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use LarkAI/codet5p-770m_nl2sql_oig with Transformers:

# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("text-generation", model="LarkAI/codet5p-770m_nl2sql_oig")

# Load model directly
from transformers import AutoTokenizer, AutoModelForSeq2SeqLM

tokenizer = AutoTokenizer.from_pretrained("LarkAI/codet5p-770m_nl2sql_oig")
model = AutoModelForSeq2SeqLM.from_pretrained("LarkAI/codet5p-770m_nl2sql_oig")

Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use LarkAI/codet5p-770m_nl2sql_oig with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "LarkAI/codet5p-770m_nl2sql_oig"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "LarkAI/codet5p-770m_nl2sql_oig",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/LarkAI/codet5p-770m_nl2sql_oig

SGLang

How to use LarkAI/codet5p-770m_nl2sql_oig 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 "LarkAI/codet5p-770m_nl2sql_oig" \
    --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": "LarkAI/codet5p-770m_nl2sql_oig",
		"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 "LarkAI/codet5p-770m_nl2sql_oig" \
        --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": "LarkAI/codet5p-770m_nl2sql_oig",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use LarkAI/codet5p-770m_nl2sql_oig with Docker Model Runner:
```
docker model run hf.co/LarkAI/codet5p-770m_nl2sql_oig
```

Data preparation and fine-tuning

by snehilsanyal - opened Jun 5, 2023

Discussion

snehilsanyal

Jun 5, 2023

Hey, @JacksonLark can you provide some information on data preparation for the OIG datasets? Also, how did you split the dataset for fine-tuning? Any supporting resources would be helpful.

JacksonLark

Lark AI org Jun 7, 2023

Hey, @JacksonLark can you provide some information on data preparation for the OIG datasets? Also, how did you split the dataset for fine-tuning? Any supporting resources would be helpful.

data preparation depends on training code. My training data like:

{
    "instruction":"Given the following schema:\nroad (road_name, state_name)\nstate (state_name, capital, population, area, country_name, density)\nhighlow (state_name, highest_point, highest_elevation, lowest_point, lowest_elevation)\nlake (lake_name, area, state_name, country_name)\nriver (river_name, length, traverse, country_name)\nborder_info (state_name, border)\nmountain (mountain_name, mountain_altitude, state_name, country_name)\ncity (city_name, state_name, population, country_name)\nWrite a SQL query to what states does the mississippi river run through",
    "input":"",
    "output":"SELECT traverse FROM river WHERE river_name = \"mississippi\" ;"
}

fine tuning, simple you can use hf example code: https://github.com/huggingface/transformers/blob/main/examples/pytorch/summarization/README.md

NikAlan

Jun 19, 2023

Do you have a lead now @snehilsanyal , as I am new to these stuffs, any help from you would be grateful.

snehilsanyal

Jul 2, 2023

@NikAlan sorry, I have been a bit busy in other works, will start again on fine-tuning, will let you know.

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