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

Libraries

How to use pearsonkyle/ArtPrompter with Transformers:

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

pipe = pipeline("text-generation", model="pearsonkyle/ArtPrompter")

# pip install -U transformers accelerate
# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("pearsonkyle/ArtPrompter")
model = AutoModelForCausalLM.from_pretrained("pearsonkyle/ArtPrompter", device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use pearsonkyle/ArtPrompter with vLLM:

Install from pip and serve model

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

Use Docker

docker model run hf.co/pearsonkyle/ArtPrompter

SGLang

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

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

pearsonkyle commited on Jan 29, 2023

Commit

6e98fea

1 Parent(s): c359678

Update README.md

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README.md +2 -2

README.md CHANGED Viewed

@@ -23,9 +23,9 @@ A [gpt2](https://huggingface.co/gpt2) powered predictive algorithm for making de
 ```python
 from transformers import pipeline
-ai = pipeline('text-generation',model='pearsonkyle/ArtPrompter', tokenizer='gpt2')
-texts = ai('The', max_length=30, num_return_sequences=5)
 for i in range(5):
     print(texts[i]['generated_text']+'\n')

 ```python
 from transformers import pipeline
+lm = pipeline('text-generation',model='pearsonkyle/ArtPrompter', tokenizer='gpt2')
+texts = lm('The', max_length=30, num_return_sequences=5)
 for i in range(5):
     print(texts[i]['generated_text']+'\n')