Instructions to use Salesforce/instructblip-vicuna-13b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use Salesforce/instructblip-vicuna-13b with Transformers:

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

pipe = pipeline("image-text-to-text", model="Salesforce/instructblip-vicuna-13b")

# Load model directly
from transformers import AutoProcessor, AutoModelForMultimodalLM

processor = AutoProcessor.from_pretrained("Salesforce/instructblip-vicuna-13b")
model = AutoModelForMultimodalLM.from_pretrained("Salesforce/instructblip-vicuna-13b")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use Salesforce/instructblip-vicuna-13b with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "Salesforce/instructblip-vicuna-13b"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Salesforce/instructblip-vicuna-13b",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/Salesforce/instructblip-vicuna-13b

SGLang

How to use Salesforce/instructblip-vicuna-13b 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/instructblip-vicuna-13b" \
    --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/instructblip-vicuna-13b",
		"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/instructblip-vicuna-13b" \
        --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/instructblip-vicuna-13b",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use Salesforce/instructblip-vicuna-13b with Docker Model Runner:
```
docker model run hf.co/Salesforce/instructblip-vicuna-13b
```

RaushanTurganbay HF Staff commited on Nov 19, 2024

Commit

3f553d4

1 Parent(s): c2ef27c

add pipeline

Browse files

Files changed (2) hide show

README.md +1 -1
config.json +0 -3

README.md CHANGED Viewed

@@ -4,7 +4,7 @@ license: other
 tags:
 - vision
 - image-captioning
-pipeline_tag: image-to-text
 ---
 # InstructBLIP model

 tags:
 - vision
 - image-captioning
+pipeline_tag: image-text-to-text
 ---
 # InstructBLIP model

config.json CHANGED Viewed

@@ -1,5 +1,4 @@
 {
-  "_name_or_path": "/raid/raushan/instructblip-vicuna-13b/",
   "architectures": [
     "InstructBlipForConditionalGeneration"
   ],
@@ -9,7 +8,6 @@
   "model_type": "instructblip",
   "num_query_tokens": 32,
   "qformer_config": {
-    "_attn_implementation_autoset": true,
     "model_type": "instructblip_qformer",
     "vocab_size": 30523
   },
@@ -46,7 +44,6 @@
   "use_decoder_only_language_model": true,
   "video_token_index": 32002,
   "vision_config": {
-    "_attn_implementation_autoset": true,
     "model_type": "instructblip_vision_model"
   }
 }

 {
   "architectures": [
     "InstructBlipForConditionalGeneration"
   ],
   "model_type": "instructblip",
   "num_query_tokens": 32,
   "qformer_config": {
     "model_type": "instructblip_qformer",
     "vocab_size": 30523
   },
   "use_decoder_only_language_model": true,
   "video_token_index": 32002,
   "vision_config": {
     "model_type": "instructblip_vision_model"
   }
 }