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

Libraries

How to use pgfeldman/Yelp_multi_cuisine with Transformers:

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

pipe = pipeline("text-generation", model="pgfeldman/Yelp_multi_cuisine")

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("pgfeldman/Yelp_multi_cuisine")
model = AutoModelForCausalLM.from_pretrained("pgfeldman/Yelp_multi_cuisine")

Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use pgfeldman/Yelp_multi_cuisine with vLLM:

Install from pip and serve model

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

Use Docker

docker model run hf.co/pgfeldman/Yelp_multi_cuisine

SGLang

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

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

A GPT-2 model finetuned on Yelp reviews downloaded from the Yelp Open Dataset. The data from this and subsamples of cuisines are used in the paper Polling Latent Opinions: A Method for Computational Sociolinguistics Using Transformer Language Models

The model is trained to produce text in response to the following prompts:

"name:"
"review:"
"stars:"

Downloads last month: 6

Paper for pgfeldman/Yelp_multi_cuisine

Polling Latent Opinions: A Method for Computational Sociolinguistics Using Transformer Language Models

Paper • 2204.07483 • Published Apr 15, 2022