Instructions to use mobilint/aya-vision-8b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use mobilint/aya-vision-8b with Transformers:

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

pipe = pipeline("image-text-to-text", model="mobilint/aya-vision-8b", trust_remote_code=True)
messages = [
    {
        "role": "user",
        "content": [
            {"type": "image", "url": "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/p-blog/candy.JPG"},
            {"type": "text", "text": "What animal is on the candy?"}
        ]
    },
]
pipe(text=messages)

# Load model directly
from transformers import AutoModelForCausalLM
model = AutoModelForCausalLM.from_pretrained("mobilint/aya-vision-8b", trust_remote_code=True, device_map="auto")

Mobilint

How to use mobilint/aya-vision-8b with Mobilint:

# pip install mblt-model-zoo
from mblt_model_zoo.vision import MBLT_Engine

model = MBLT_Engine(
    model_cls="aya-vision-8b",
    model_type="DEFAULT",
    model_path="",
    core_mode="global8",
)

try:
    image = model.preprocess("path/to/image.jpg")
    output = model(image)
    result = model.postprocess(output)
finally:
    model.dispose()

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use mobilint/aya-vision-8b with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "mobilint/aya-vision-8b"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "mobilint/aya-vision-8b",
		"messages": [
			{
				"role": "user",
				"content": [
					{
						"type": "text",
						"text": "Describe this image in one sentence."
					},
					{
						"type": "image_url",
						"image_url": {
							"url": "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg"
						}
					}
				]
			}
		]
	}'

Use Docker

docker model run hf.co/mobilint/aya-vision-8b

SGLang

How to use mobilint/aya-vision-8b 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 "mobilint/aya-vision-8b" \
    --host 0.0.0.0 \
    --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "mobilint/aya-vision-8b",
		"messages": [
			{
				"role": "user",
				"content": [
					{
						"type": "text",
						"text": "Describe this image in one sentence."
					},
					{
						"type": "image_url",
						"image_url": {
							"url": "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg"
						}
					}
				]
			}
		]
	}'

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 "mobilint/aya-vision-8b" \
        --host 0.0.0.0 \
        --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "mobilint/aya-vision-8b",
		"messages": [
			{
				"role": "user",
				"content": [
					{
						"type": "text",
						"text": "Describe this image in one sentence."
					},
					{
						"type": "image_url",
						"image_url": {
							"url": "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg"
						}
					}
				]
			}
		]
	}'

Docker Model Runner
How to use mobilint/aya-vision-8b with Docker Model Runner:
```
docker model run hf.co/mobilint/aya-vision-8b
```

About

This repository provides a model compiled and optimized for Mobilint NPU hardware.
The model is packaged for deployment on Mobilint’s acceleration stack and is intended to be used within that environment.

Downloads last month: 89

Safetensors

Model size

1B params

Tensor type

F16

Model tree for mobilint/aya-vision-8b

Base model

CohereLabs/aya-vision-8b

Quantized

(3)

this model

Collection including mobilint/aya-vision-8b

Cohere Labs

Collection

2 items • Updated Jun 25