How to use from
llama.cppInstall from WinGet (Windows)
winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf Jooju2872/moondream2:F16# Run inference directly in the terminal:
llama-cli -hf Jooju2872/moondream2:F16Use pre-built binary
# Download pre-built binary from:
# https://github.com/ggerganov/llama.cpp/releases# Start a local OpenAI-compatible server with a web UI:
./llama-server -hf Jooju2872/moondream2:F16# Run inference directly in the terminal:
./llama-cli -hf Jooju2872/moondream2:F16Build from source code
git clone https://github.com/ggerganov/llama.cpp.git
cd llama.cpp
cmake -B build
cmake --build build -j --target llama-server llama-cli# Start a local OpenAI-compatible server with a web UI:
./build/bin/llama-server -hf Jooju2872/moondream2:F16# Run inference directly in the terminal:
./build/bin/llama-cli -hf Jooju2872/moondream2:F16Use Docker
docker model run hf.co/Jooju2872/moondream2:F16Quick Links
moondream is a small vision language model designed to run efficiently on edge devices. Check out the GitHub repository for details, or try it out on the Hugging Face Space!
This model works on lower Torch version(2.1.1) and adds
temperatureandtop_pparameters.
Benchmarks
| Release | VQAv2 | GQA | TextVQA | DocVQA | TallyQA (simple/full) |
POPE (rand/pop/adv) |
|---|---|---|---|---|---|---|
| 2024-08-26 (latest) | 80.3 | 64.3 | 65.2 | 70.5 | 82.6 / 77.6 | 89.6 / 88.8 / 87.2 |
| 2024-07-23 | 79.4 | 64.9 | 60.2 | 61.9 | 82.0 / 76.8 | 91.3 / 89.7 / 86.9 |
| 2024-05-20 | 79.4 | 63.1 | 57.2 | 30.5 | 82.1 / 76.6 | 91.5 / 89.6 / 86.2 |
| 2024-05-08 | 79.0 | 62.7 | 53.1 | 30.5 | 81.6 / 76.1 | 90.6 / 88.3 / 85.0 |
| 2024-04-02 | 77.7 | 61.7 | 49.7 | 24.3 | 80.1 / 74.2 | - |
| 2024-03-13 | 76.8 | 60.6 | 46.4 | 22.2 | 79.6 / 73.3 | - |
| 2024-03-06 | 75.4 | 59.8 | 43.1 | 20.9 | 79.5 / 73.2 | - |
| 2024-03-04 | 74.2 | 58.5 | 36.4 | - | - | - |
Usage
pip install transformers einops
from transformers import AutoModelForCausalLM, AutoTokenizer
from PIL import Image
model_id = "vikhyatk/moondream2"
revision = "2024-08-26"
model = AutoModelForCausalLM.from_pretrained(
model_id, trust_remote_code=True, revision=revision
)
tokenizer = AutoTokenizer.from_pretrained(model_id, revision=revision)
image = Image.open('<IMAGE_PATH>')
enc_image = model.encode_image(image)
print(model.answer_question(enc_image, "Describe this image.", tokenizer))
The model is updated regularly, so we recommend pinning the model version to a specific release as shown above.
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Install from brew
# Start a local OpenAI-compatible server with a web UI: llama-server -hf Jooju2872/moondream2:F16# Run inference directly in the terminal: llama-cli -hf Jooju2872/moondream2:F16