Image-Text-to-Text
Transformers
Safetensors
Arabic
ar-cxr
feature-extraction
medical
radiology
chest-xray
arabic
vision-language
report-generation
lora
rad-dino
falcon-h1
not-for-clinical-use
custom_code
Eval Results (legacy)
Instructions to use Vionex-digital/Ar-CXR with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Vionex-digital/Ar-CXR with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-text-to-text", model="Vionex-digital/Ar-CXR", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Vionex-digital/Ar-CXR", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use Vionex-digital/Ar-CXR with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "Vionex-digital/Ar-CXR" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Vionex-digital/Ar-CXR", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/Vionex-digital/Ar-CXR
- SGLang
How to use Vionex-digital/Ar-CXR 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 "Vionex-digital/Ar-CXR" \ --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": "Vionex-digital/Ar-CXR", "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 "Vionex-digital/Ar-CXR" \ --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": "Vionex-digital/Ar-CXR", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use Vionex-digital/Ar-CXR with Docker Model Runner:
docker model run hf.co/Vionex-digital/Ar-CXR
Ar-CXR: two-connector release (Q-Former generation + MLP grounding), verified faithful
8544f77 verified |
Download LICENSE.md from Vionex-digital/Ar-CXR: direct link, hf CLI and curl.
- Browser
- Download file 1.69 kB
-
https://huggingface.co/Vionex-digital/Ar-CXR/resolve/main/LICENSE.md
- Command line
-
hf download hf://Vionex-digital/Ar-CXR/LICENSE.md
-
curl -L -o LICENSE.md https://huggingface.co/Vionex-digital/Ar-CXR/resolve/main/LICENSE.md
1.69 kB
| # Ar-CXR License (composite, research-only) | |
| Ar-CXR is **not** distributed under a single permissive license. It is a derivative | |
| of multiple components, each with its own terms. **You must comply with all of the | |
| upstream licenses below, and with the most restrictive where they overlap.** | |
| ## 1. Ar-CXR adapters & code (this repository) | |
| The trained adapters (`weights/`), configuration, and code (`modeling_ar_cxr.py`, | |
| `export_to_hf.py`) are released by Vionex Digital Solutions **for non-commercial | |
| academic research only**, with no warranty. They are **not** a medical device and | |
| must not be used for clinical decision-making. Redistribution must retain this | |
| notice and the disclaimers in `README.md` and `NOTICE.md`. | |
| ## 2. Decoder base — Falcon-H1-7B-Instruct | |
| `tiiuae/Falcon-H1-7B-Instruct` is governed by the **TII Falcon-LLM License 2.0**. | |
| You must accept and comply with it to download and use the base decoder: | |
| https://huggingface.co/tiiuae/Falcon-H1-7B-Instruct | |
| ## 3. Vision base — RAD-DINO-MAIRA-2 | |
| `microsoft/rad-dino-maira-2` is governed by its **Microsoft Research license** | |
| (research use). You must accept and comply with it to download and use the base | |
| vision encoder: | |
| https://huggingface.co/microsoft/rad-dino-maira-2 | |
| ## 4. Training data — CheXpert-Plus | |
| Ar-CXR was trained on derivatives of **CheXpert-Plus**, governed by the Stanford | |
| CheXpert-Plus **Data Use Agreement**. The translated training corpus is **not** | |
| redistributed in this repository. The CheXpert-Plus terms (non-commercial | |
| research, no re-identification, no redistribution of the imaging data) extend to | |
| models and derivatives trained on it. | |
| By downloading or using Ar-CXR you agree to all of the above. | |