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

Libraries

How to use nirajsaran/AdTextGenerator with Transformers:

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

pipe = pipeline("text-generation", model="nirajsaran/AdTextGenerator")

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("nirajsaran/AdTextGenerator")
model = AutoModelForCausalLM.from_pretrained("nirajsaran/AdTextGenerator")

Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use nirajsaran/AdTextGenerator with vLLM:

Install from pip and serve model

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

Use Docker

docker model run hf.co/nirajsaran/AdTextGenerator

SGLang

How to use nirajsaran/AdTextGenerator 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 "nirajsaran/AdTextGenerator" \
    --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": "nirajsaran/AdTextGenerator",
		"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 "nirajsaran/AdTextGenerator" \
        --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": "nirajsaran/AdTextGenerator",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use nirajsaran/AdTextGenerator with Docker Model Runner:
```
docker model run hf.co/nirajsaran/AdTextGenerator
```

Generates Ad text copy, for ads for Amazon shopping (fine tuned for electronics and wearables).

The model is fine tuned on the EleutherAI/gpt-neo-125M model using the Amazon Ads dataset.

Usage Examples:
Select from among the examples in the dropdown or enter your own prompts.

You can try entering brand and product names like Samsung Galaxy to see the ad text generator in action.

Feel free to play around with native Amazon ads which are product descriptions like: Sony BDPS3700 Streaming Blu-Ray Disc Player with Wi-Fi (Black).
AmazonBasics TV Trolley for 24-43" TVs with Swivel Feature.

Or try additional ad formats, similar to other shopping sites for holiday deals, like:
Big savings on the new Roku Streaming Device
Mothers Day discounts for Apple Watch Wireless Charger USB Charging Cable
Last minute shopping for Samsung headphones for

Model Performance:
The model does quite well on the Electronics and Wearables categories on which it has been fine-tuned. There are, however, occasional hallucinations, though the ad copy is mostly coherent.

In other domains, it doesn't do quite as well...
Halloween Tesla is
Honda on sale

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