Instructions to use Image-Captioning-ML/Vit-GPT2-COCO2017Flickr-02 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use Image-Captioning-ML/Vit-GPT2-COCO2017Flickr-02 with Transformers:

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

pipe = pipeline("image-text-to-text", model="Image-Captioning-ML/Vit-GPT2-COCO2017Flickr-02")

# Load model directly
from transformers import AutoTokenizer, AutoModelForMultimodalLM

tokenizer = AutoTokenizer.from_pretrained("Image-Captioning-ML/Vit-GPT2-COCO2017Flickr-02")
model = AutoModelForMultimodalLM.from_pretrained("Image-Captioning-ML/Vit-GPT2-COCO2017Flickr-02", device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use Image-Captioning-ML/Vit-GPT2-COCO2017Flickr-02 with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "Image-Captioning-ML/Vit-GPT2-COCO2017Flickr-02"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Image-Captioning-ML/Vit-GPT2-COCO2017Flickr-02",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/Image-Captioning-ML/Vit-GPT2-COCO2017Flickr-02

SGLang

How to use Image-Captioning-ML/Vit-GPT2-COCO2017Flickr-02 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 "Image-Captioning-ML/Vit-GPT2-COCO2017Flickr-02" \
    --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": "Image-Captioning-ML/Vit-GPT2-COCO2017Flickr-02",
		"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 "Image-Captioning-ML/Vit-GPT2-COCO2017Flickr-02" \
        --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": "Image-Captioning-ML/Vit-GPT2-COCO2017Flickr-02",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use Image-Captioning-ML/Vit-GPT2-COCO2017Flickr-02 with Docker Model Runner:
```
docker model run hf.co/Image-Captioning-ML/Vit-GPT2-COCO2017Flickr-02
```

NourFakih commited on May 20, 2024

Commit

ec85a68

verified ·

1 Parent(s): d4e6048

Training in progress, step 19500

Browse files

Files changed (2) hide show

model.safetensors +1 -1
runs/May20_11-10-15_90603e6ec558/events.out.tfevents.1716203431.90603e6ec558.34.3 +2 -2

model.safetensors CHANGED Viewed

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:f5df2d439023e1aa6a61a969b28137ed7e314e8b1243e65ba2904f08d6fbca87
 size 956835520

 version https://git-lfs.github.com/spec/v1
+oid sha256:efd7693456491d861c5d3eacde04ad23f196ec2009291714845819f13a2aea3c
 size 956835520

runs/May20_11-10-15_90603e6ec558/events.out.tfevents.1716203431.90603e6ec558.34.3 CHANGED Viewed

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:4dc61772029d660e4623ac54660a89bf14bc2e4687ecbc5f82117d6bbdddcaed
-size 9957

 version https://git-lfs.github.com/spec/v1
+oid sha256:0a722c0fdf3576e5f4d80b0f352dbb247b0971a806f831337b0953ceff0f2ee0
+size 11067