Instructions to use alibaba-pai/pai-bloom-1b1-text2prompt-sd-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use alibaba-pai/pai-bloom-1b1-text2prompt-sd-v2 with Transformers:

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

pipe = pipeline("text-generation", model="alibaba-pai/pai-bloom-1b1-text2prompt-sd-v2")

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("alibaba-pai/pai-bloom-1b1-text2prompt-sd-v2")
model = AutoModelForCausalLM.from_pretrained("alibaba-pai/pai-bloom-1b1-text2prompt-sd-v2")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use alibaba-pai/pai-bloom-1b1-text2prompt-sd-v2 with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "alibaba-pai/pai-bloom-1b1-text2prompt-sd-v2"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "alibaba-pai/pai-bloom-1b1-text2prompt-sd-v2",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/alibaba-pai/pai-bloom-1b1-text2prompt-sd-v2

SGLang

How to use alibaba-pai/pai-bloom-1b1-text2prompt-sd-v2 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 "alibaba-pai/pai-bloom-1b1-text2prompt-sd-v2" \
    --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": "alibaba-pai/pai-bloom-1b1-text2prompt-sd-v2",
		"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 "alibaba-pai/pai-bloom-1b1-text2prompt-sd-v2" \
        --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": "alibaba-pai/pai-bloom-1b1-text2prompt-sd-v2",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use alibaba-pai/pai-bloom-1b1-text2prompt-sd-v2 with Docker Model Runner:
```
docker model run hf.co/alibaba-pai/pai-bloom-1b1-text2prompt-sd-v2
```

chywang commited on Mar 6, 2024

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	@@ -77,3 +77,23 @@ table th:nth-of-type(2) {
77
78	If you want to use this model, please read this [document](https://terms.alicdn.com/legal-agreement/terms/common_platform_service/20230505180457947/20230505180457947.html) carefully and abide by the terms.
79

 If you want to use this model, please read this [document](https://terms.alicdn.com/legal-agreement/terms/common_platform_service/20230505180457947/20230505180457947.html) carefully and abide by the terms.
+## Paper Citation
+If you find the model useful, please consider cite the paper:
+```
+@inproceedings{emnlp2023a,
+  author    = {Tingfeng Cao and
+            Chengyu Wang and
+            Bingyan Liu and
+            Ziheng Wu and
+            Jinhui Zhu and
+            Jun Huang},
+  title     = {BeautifulPrompt: Towards Automatic Prompt Engineering for Text-to-Image Synthesis},
+  booktitle = {Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing: Industry Track},
+  pages     = {1--11},
+  year      = {2023}
+}
+```