Image-Text-to-Text
Transformers
PyTorch
Safetensors
English
blip-2
visual-question-answering
vision
image-to-text
image-captioning
Instructions to use Salesforce/blip2-opt-2.7b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
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, AutoModelForMultimodalLM processor = AutoProcessor.from_pretrained("Salesforce/blip2-opt-2.7b") model = AutoModelForMultimodalLM.from_pretrained("Salesforce/blip2-opt-2.7b") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- 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
fix cpu example
#6
by devneko - opened
README.md
CHANGED
|
@@ -67,9 +67,9 @@ For code examples, we refer to the [documentation](https://huggingface.co/docs/t
|
|
| 67 |
```python
|
| 68 |
import requests
|
| 69 |
from PIL import Image
|
| 70 |
-
from transformers import
|
| 71 |
|
| 72 |
-
processor =
|
| 73 |
model = Blip2ForConditionalGeneration.from_pretrained("Salesforce/blip2-opt-2.7b")
|
| 74 |
|
| 75 |
img_url = 'https://storage.googleapis.com/sfr-vision-language-research/BLIP/demo.jpg'
|
|
|
|
| 67 |
```python
|
| 68 |
import requests
|
| 69 |
from PIL import Image
|
| 70 |
+
from transformers import Blip2Processor, Blip2ForConditionalGeneration
|
| 71 |
|
| 72 |
+
processor = Blip2Processor.from_pretrained("Salesforce/blip2-opt-2.7b")
|
| 73 |
model = Blip2ForConditionalGeneration.from_pretrained("Salesforce/blip2-opt-2.7b")
|
| 74 |
|
| 75 |
img_url = 'https://storage.googleapis.com/sfr-vision-language-research/BLIP/demo.jpg'
|