Instructions to use avatarcontinues/imagedata with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use avatarcontinues/imagedata with Transformers:

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

pipe = pipeline("image-text-to-text", model="avatarcontinues/imagedata")

# pip install -U transformers accelerate
# Load model directly
from transformers import AutoProcessor, AutoModelForMultimodalLM

processor = AutoProcessor.from_pretrained("avatarcontinues/imagedata")
model = AutoModelForMultimodalLM.from_pretrained("avatarcontinues/imagedata", device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use avatarcontinues/imagedata with vLLM:

Install from pip and serve model

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

Use Docker

docker model run hf.co/avatarcontinues/imagedata

SGLang

How to use avatarcontinues/imagedata 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 "avatarcontinues/imagedata" \
    --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": "avatarcontinues/imagedata",
		"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 "avatarcontinues/imagedata" \
        --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": "avatarcontinues/imagedata",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use avatarcontinues/imagedata with Docker Model Runner:
```
docker model run hf.co/avatarcontinues/imagedata
```

avatarcontinues commited on Sep 15, 2023

Commit

8d3be5b

1 Parent(s): ae56644

Upload BlipForConditionalGeneration

Browse files

Files changed (1) hide show

pytorch_model.bin +1 -1

pytorch_model.bin CHANGED Viewed

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:987fd55ae61c7d06995e2f6832b8f287c7e3612175802b1c51e814808c6309d2
 size 989816429

 version https://git-lfs.github.com/spec/v1
+oid sha256:5f2766e5a76f6bf36db0582d8041a5c752659d10b24fd4ab31e8cfb7729af8f8
 size 989816429