Instructions to use Duyen1rt/git-base-caption with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use Duyen1rt/git-base-caption with Transformers:

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

pipe = pipeline("image-text-to-text", model="Duyen1rt/git-base-caption")

# Load model directly
from transformers import AutoProcessor, AutoModelForImageTextToText

processor = AutoProcessor.from_pretrained("Duyen1rt/git-base-caption")
model = AutoModelForImageTextToText.from_pretrained("Duyen1rt/git-base-caption")

Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use Duyen1rt/git-base-caption with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "Duyen1rt/git-base-caption"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Duyen1rt/git-base-caption",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/Duyen1rt/git-base-caption

SGLang

How to use Duyen1rt/git-base-caption 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 "Duyen1rt/git-base-caption" \
    --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": "Duyen1rt/git-base-caption",
		"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 "Duyen1rt/git-base-caption" \
        --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": "Duyen1rt/git-base-caption",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use Duyen1rt/git-base-caption with Docker Model Runner:
```
docker model run hf.co/Duyen1rt/git-base-caption
```

git-base-caption / model.safetensors

Duyen1rt

Training in progress, step 50

ea0370e verified over 1 year ago

download

history blame contribute delete

707 MB

This file is stored with Xet . It is too big to display, but you can still download it.

Xet Pointer Details

( Raw pointer file )

Xet hash:: 8f46b2315440e25a29726118116d5cb999e7585a957046374fd050877b3d7450
Size of remote file:: 707 MB
SHA256:: afd1ba5d7fc493aaeb99c12e935f6a2d6e03329d27b15a322faf524fca86cf03

Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.