Instructions to use flax-community/Image-captioning-Indonesia with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use flax-community/Image-captioning-Indonesia with Transformers:

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

pipe = pipeline("text-generation", model="flax-community/Image-captioning-Indonesia")

# Load model directly
from transformers import AutoModelForSeq2SeqLM
model = AutoModelForSeq2SeqLM.from_pretrained("flax-community/Image-captioning-Indonesia", dtype="auto")

Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use flax-community/Image-captioning-Indonesia with vLLM:

Install from pip and serve model

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

Use Docker

docker model run hf.co/flax-community/Image-captioning-Indonesia

SGLang

How to use flax-community/Image-captioning-Indonesia 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 "flax-community/Image-captioning-Indonesia" \
    --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": "flax-community/Image-captioning-Indonesia",
		"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 "flax-community/Image-captioning-Indonesia" \
        --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": "flax-community/Image-captioning-Indonesia",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use flax-community/Image-captioning-Indonesia with Docker Model Runner:
```
docker model run hf.co/flax-community/Image-captioning-Indonesia
```

acul3 commited on Jul 19, 2021

Commit

1865061

1 Parent(s): 57929b3

Update README.md

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@@ -62,7 +62,7 @@ print(generated_ids)
 ```
 ## Training data
-To be added.
 ## Training procedure
 The model was trained on a TPUv3-8 VM provided by the Google Cloud team.

 ```
 ## Training data
+The Model was trained on translated Coco,Flickr and ViZWiz, each of them were translated using google translate and marian mt. we took only random 2 captions per image for each datasets
 ## Training procedure
 The model was trained on a TPUv3-8 VM provided by the Google Cloud team.