Instructions to use AquilaX-AI/NL-JSON-Start-Scan with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use AquilaX-AI/NL-JSON-Start-Scan with Transformers:

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

pipe = pipeline("text-generation", model="AquilaX-AI/NL-JSON-Start-Scan")

# Load model directly
from transformers import AutoTokenizer, AutoModelForSeq2SeqLM

tokenizer = AutoTokenizer.from_pretrained("AquilaX-AI/NL-JSON-Start-Scan")
model = AutoModelForSeq2SeqLM.from_pretrained("AquilaX-AI/NL-JSON-Start-Scan", device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use AquilaX-AI/NL-JSON-Start-Scan with vLLM:

Install from pip and serve model

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

Use Docker

docker model run hf.co/AquilaX-AI/NL-JSON-Start-Scan

SGLang

How to use AquilaX-AI/NL-JSON-Start-Scan 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 "AquilaX-AI/NL-JSON-Start-Scan" \
    --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": "AquilaX-AI/NL-JSON-Start-Scan",
		"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 "AquilaX-AI/NL-JSON-Start-Scan" \
        --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": "AquilaX-AI/NL-JSON-Start-Scan",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use AquilaX-AI/NL-JSON-Start-Scan with Docker Model Runner:
```
docker model run hf.co/AquilaX-AI/NL-JSON-Start-Scan
```

suriya7 commited on Jul 29, 2024

Commit

45f315b

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1 Parent(s): cd3009f

Update README.md

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@@ -21,7 +21,7 @@ The AquilaX-NL-JSON-Start-Scan model is designed to interpret natural language q
 # Getting Started
 ## Usage
-Below we share some code snippets on how to get quickly started with running the model. First make sure to pip install -U transformers[torch], then copy the snippet from the section.
 ## Requirements
 ```bash
@@ -128,11 +128,11 @@ print(f"Time taken: {end - start}")
 ```
 ## License
-This project is licensed under the Apache 2.0 License - see the LICENSE file for details.
 ## Authors
 - [Aquilax-Ai](https://huggingface.co/AquilaX-AI)
 ## Acknowledgments
-- Hugging Face for the Transformers library.
-- Any other acknowledgments.

 # Getting Started
 ## Usage
+Below we share some code snippets on how to get quickly started with running the model. First make sure to `pip install -U transformers[torch]`, then copy the snippet from the section.
 ## Requirements
 ```bash
 ```
 ## License
+This project is licensed under the Apache 2.0 License - see the [LICENSE](LICENSE) file for details.
 ## Authors
 - [Aquilax-Ai](https://huggingface.co/AquilaX-AI)
 ## Acknowledgments
+- Hugging Face for the Transformers library.