Image-Text-to-Text
Transformers
Safetensors
English
Chinese
sensenova_loop
text-generation
nvfp4
modelopt
quantized
multimodal
looped-transformer
mhc
mtp
custom_code
conversational
8-bit precision
Instructions to use gitcommit90/SenseNova-Loop-9B-Preview-NVFP4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use gitcommit90/SenseNova-Loop-9B-Preview-NVFP4 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-text-to-text", model="gitcommit90/SenseNova-Loop-9B-Preview-NVFP4", 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)# pip install -U transformers accelerate # Load model directly from transformers import AutoModelForCausalLM model = AutoModelForCausalLM.from_pretrained("gitcommit90/SenseNova-Loop-9B-Preview-NVFP4", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use gitcommit90/SenseNova-Loop-9B-Preview-NVFP4 with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "gitcommit90/SenseNova-Loop-9B-Preview-NVFP4" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "gitcommit90/SenseNova-Loop-9B-Preview-NVFP4", "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/gitcommit90/SenseNova-Loop-9B-Preview-NVFP4
- SGLang
How to use gitcommit90/SenseNova-Loop-9B-Preview-NVFP4 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 "gitcommit90/SenseNova-Loop-9B-Preview-NVFP4" \ --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": "gitcommit90/SenseNova-Loop-9B-Preview-NVFP4", "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 "gitcommit90/SenseNova-Loop-9B-Preview-NVFP4" \ --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": "gitcommit90/SenseNova-Loop-9B-Preview-NVFP4", "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 gitcommit90/SenseNova-Loop-9B-Preview-NVFP4 with Docker Model Runner:
docker model run hf.co/gitcommit90/SenseNova-Loop-9B-Preview-NVFP4
|
Download figures/quality-summary.svg from gitcommit90/SenseNova-Loop-9B-Preview-NVFP4: direct link, hf CLI and curl.
- Browser
- Download file 27.8 kB
-
https://huggingface.co/gitcommit90/SenseNova-Loop-9B-Preview-NVFP4/resolve/main/figures/quality-summary.svg
- Command line
-
hf download hf://gitcommit90/SenseNova-Loop-9B-Preview-NVFP4/figures/quality-summary.svg
-
curl -L -o quality-summary.svg https://huggingface.co/gitcommit90/SenseNova-Loop-9B-Preview-NVFP4/resolve/main/figures/quality-summary.svg
27.8 kB
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| <text style="font-size: 10px; font-family: 'DejaVu Sans', 'Arial', 'Helvetica', sans-serif; fill: #4d4d4d" transform="translate(292.029844 393.881375)">Pooled accuracy: BF16 82.7% → NVFP4 83.0% • Δ +0.3 pp [−3.0, +4.0]</text> | |
| <text style="font-size: 10px; font-family: 'DejaVu Sans', 'Arial', 'Helvetica', sans-serif; fill: #4d4d4d" transform="translate(246.447812 410.381375)">*IFEval subset uses a re-implemented checker. **Tools: 20 hand-written BFCL-style cases.</text> | |
| <text style="font-size: 10px; font-family: 'DejaVu Sans', 'Arial', 'Helvetica', sans-serif; fill: #4d4d4d" transform="translate(211.643906 426.881375)">Subsets of 20–80 items/task; uncertainty is wide. No claim of losslessness or intelligence improvement.</text> | |
| <text style="font-size: 10px; font-family: 'DejaVu Sans', 'Arial', 'Helvetica', sans-serif; fill: #4d4d4d" transform="translate(245.354062 443.242312)">Source: evaluation/compare_vs_ref.json; see model card for truncations and methodology.</text> | |
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