Instructions to use mindlab-research/MJev-Spatial-4B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use mindlab-research/MJev-Spatial-4B with Transformers:

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

pipe = pipeline("image-text-to-text", model="mindlab-research/MJev-Spatial-4B")

# pip install -U transformers accelerate
# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("mindlab-research/MJev-Spatial-4B", device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use mindlab-research/MJev-Spatial-4B with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "mindlab-research/MJev-Spatial-4B"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "mindlab-research/MJev-Spatial-4B",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/mindlab-research/MJev-Spatial-4B

SGLang

How to use mindlab-research/MJev-Spatial-4B 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 "mindlab-research/MJev-Spatial-4B" \
    --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": "mindlab-research/MJev-Spatial-4B",
		"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 "mindlab-research/MJev-Spatial-4B" \
        --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": "mindlab-research/MJev-Spatial-4B",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use mindlab-research/MJev-Spatial-4B with Docker Model Runner:
```
docker model run hf.co/mindlab-research/MJev-Spatial-4B
```

fix formulation and add citation

by Fr0zencr4nE - opened 23 days ago

base: refs/heads/main

←

from: refs/pr/1

Discussion Files changed

-7

Files changed (1) hide show

README.md +1 -7

README.md CHANGED Viewed

@@ -1,9 +1,3 @@
----
-license: apache-2.0
-library_name: transformers
-pipeline_tag: image-text-to-text
----
 <div align="center">
 # ![MJev-Spatial: System One Spatial Intelligence via Native Attention Matching](assets/mjev-spatial-title.png)
@@ -221,4 +215,4 @@ If you find this work useful, please cite:
 ## LICENSE
-The source code is released under the Apache License 2.0. See [LICENSE](LICENSE) and [NOTICE](NOTICE) for third-party attribution.

 <div align="center">
 # ![MJev-Spatial: System One Spatial Intelligence via Native Attention Matching](assets/mjev-spatial-title.png)
 ## LICENSE
+The source code is released under the Apache License 2.0. See [LICENSE](LICENSE) and [NOTICE](NOTICE) for third-party attribution.