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
```

Seeking resources to perform multimodal semantic search

#41

by LukaBloomRox - opened Jan 5, 2025

Discussion

LukaBloomRox

Jan 5, 2025

Hello,

I’m Myles, an applied scientist looking to build on LAVIS BLIP-2 in order to create multimodal embeddings on objects that contain images and structured text input derived from training videos in the wheelchair and mobility device custom seating sector. BLIP-2 stands out due to its higher input context window as compared to OpenClip or ViLT.

I’m considering BLIP-2 due to its cross-attention focus as I need to perform multimodal semantic searches across the latent semantic embedding space.

I’m considering use of PineCone to actuate this plan.

I lack the experience and resources to successfully perform fine tuning at this stage so am looking to the community for building blocks that will allow me to move forward and create value.

Discussion welcome /!encouraged.

This journey is chronicled in:

https://ai.stackexchange.com/questions/40753/how-to-generate-original-training-videos-based-on-existing-videoset

Also posted in https://huggingface.co/thisisiron/lavis-blip2-qformer/discussions/1

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