Instructions to use leloy/Anole-7b-v0.1-hf with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use leloy/Anole-7b-v0.1-hf with Transformers:

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

pipe = pipeline("image-text-to-text", model="leloy/Anole-7b-v0.1-hf")

# Load model directly
from transformers import AutoProcessor, AutoModelForMultimodalLM

processor = AutoProcessor.from_pretrained("leloy/Anole-7b-v0.1-hf")
model = AutoModelForMultimodalLM.from_pretrained("leloy/Anole-7b-v0.1-hf", device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use leloy/Anole-7b-v0.1-hf with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "leloy/Anole-7b-v0.1-hf"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "leloy/Anole-7b-v0.1-hf",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/leloy/Anole-7b-v0.1-hf

SGLang

How to use leloy/Anole-7b-v0.1-hf 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 "leloy/Anole-7b-v0.1-hf" \
    --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": "leloy/Anole-7b-v0.1-hf",
		"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 "leloy/Anole-7b-v0.1-hf" \
        --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": "leloy/Anole-7b-v0.1-hf",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use leloy/Anole-7b-v0.1-hf with Docker Model Runner:
```
docker model run hf.co/leloy/Anole-7b-v0.1-hf
```
Browse Quantizations to use this model in llama.cpp, Ollama, LM Studio, or any compatible app.

Anole: An Open, Autoregressive and Native Multimodal Models for Interleaved Image-Text Generation

Note: This is a huggingface-compatible version of the model converted by leloy. Currently only works on this branch of the Transformers library.

Anole is the first open-source, autoregressive, and natively trained large multimodal model capable of interleaved image-text generation (without using stable diffusion). While it builds upon the strengths of Chameleon, Anole excels at the complex task of generating coherent sequences of alternating text and images. Through an innovative fine-tuning process using a carefully curated dataset of approximately 6,000 images, Anole achieves remarkable image generation and understanding capabilities with minimal additional training. This efficient approach, combined with its open-source nature, positions Anole as a catalyst for accelerated research and development in multimodal AI. Preliminary tests demonstrate Anole's exceptional ability to follow nuanced instructions, producing high-quality images and interleaved text-image content that closely aligns with user prompts.

The major functionalities of Anole are listed below:

Interleaved Text-Image Structured Generation (support added by leloy)
Text-to-Image Generation
Interleaved Text-Image Generation
Text Generation
MultiModal Understanding

where Bold represents newly added capabilities on the basis of Chameleon.

Please refer to our github repo for examples generated by Anole!

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Safetensors

Model size

7B params

Tensor type

F32

BF16

Inference Providers NEW

Image-Text-to-Text

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Anole: An Open, Autoregressive and Native Multimodal Models for Interleaved Image-Text Generation

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