Instructions to use Salesforce/blip2-opt-2.7b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use Salesforce/blip2-opt-2.7b with Transformers:

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

pipe = pipeline("image-text-to-text", model="Salesforce/blip2-opt-2.7b")

# Load model directly
from transformers import AutoProcessor, AutoModelForVisualQuestionAnswering

processor = AutoProcessor.from_pretrained("Salesforce/blip2-opt-2.7b")
model = AutoModelForVisualQuestionAnswering.from_pretrained("Salesforce/blip2-opt-2.7b")

Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use Salesforce/blip2-opt-2.7b with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "Salesforce/blip2-opt-2.7b"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Salesforce/blip2-opt-2.7b",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/Salesforce/blip2-opt-2.7b

SGLang

How to use Salesforce/blip2-opt-2.7b 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 "Salesforce/blip2-opt-2.7b" \
    --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": "Salesforce/blip2-opt-2.7b",
		"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 "Salesforce/blip2-opt-2.7b" \
        --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": "Salesforce/blip2-opt-2.7b",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use Salesforce/blip2-opt-2.7b with Docker Model Runner:
```
docker model run hf.co/Salesforce/blip2-opt-2.7b
```

Invoking SageMaker endpoint with BLIP2 model?

#10

by CowboyWay - opened Jun 23, 2023

Discussion

CowboyWay

Jun 23, 2023

I followed the deploy instructions to host the blip2 model in a SageMaker endpoint. However, it's unclear how to go about calling an inference with an image and prompt? Do you use the HF predictor class or the SageMaker runtime client? What are the correct methods to structure the payload for each (if both work)? The use case is with AWS Lambda and the examples provided don't cover this well.

thanks!

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