fix readme

README.md

@@ -18,6 +18,52 @@ For image understanding, NLD-Uni encodes images into continuous visual features
 
 This card describes the NLD-Uni architecture generally.
 
+## Environment
+
+Install the dependencies in `requirements.txt` with Python 3.13 and CUDA 12.6. Install PyTorch before building FlashAttention:
+
+```bash
+pip install -r requirements.txt
+pip install --no-build-isolation flash-attn==2.8.0.post2
+```
+
+Validated on an NVIDIA H100 80 GB. The eight BF16 weight shards contain all 1,557 active model tensors. `weights_manifest.json` records their hashes.
+
+## Python inference
+
+```python
+import torch
+from transformers import AutoModelForCausalLM
+
+model = AutoModelForCausalLM.from_pretrained(
+    '/path/to/hf_checkpoint',  # or 'organization/model-name'
+    trust_remote_code=True,
+    torch_dtype=torch.bfloat16,
+).to('cuda').eval()
+
+image = model.text_to_image('A red ceramic mug on a wooden table.', seed=42)
+image.save('mug.png')
+
+edited = model.image_edit(image, 'Change the mug to blue.', seed=42)
+edited.save('blue_mug.png')
+
+answer = model.generate('What color is the mug?', image=edited)
+print(answer)
+```
+
+Image inputs accept Pillow images or local file paths. Image methods return Pillow images; `generate` returns text by default. Token IDs can be supplied through `input_ids` for text prompts, and `return_token_ids=True` returns the generated token tensor. The `inference.py` command exposes each task.
+
+## Minimal command-line inference
+
+```bash
+python inference.py /path/to/hf_checkpoint --task t2i --prompt 'A red mug.' --output mug.png
+python inference.py /path/to/hf_checkpoint --task edit --image mug.png --prompt 'Make the mug blue.' --output blue.png
+python inference.py /path/to/hf_checkpoint --task understand --image blue.png --prompt 'What color is the mug?'
+```
+
+Replace the model argument with the published Hugging Face model ID for remote loading. The standalone script only uses Transformers and this repository's model code.
+
+
 ### License/Terms of Use
 
 GOVERNING TERMS: Use of this model is governed by the [NVIDIA Open Source License Agreement](https://huggingface.co/nvidia/NL-Diffusion-Image/raw/main/LICENSE).
@@ -181,47 +227,3 @@ Users are responsible for model inputs and outputs and for implementing appropri
 
 Report model quality concerns, security vulnerabilities, or NVIDIA AI concerns through [NVIDIA’s reporting channel](https://www.nvidia.com/en-us/support/submit-security-vulnerability/).
 
-## Environment
-
-Install the dependencies in `requirements.txt` with Python 3.13 and CUDA 12.6. Install PyTorch before building FlashAttention:
-
-```bash
-pip install -r requirements.txt
-pip install --no-build-isolation flash-attn==2.8.0.post2
-```
-
-Validated on an NVIDIA H100 80 GB. The eight BF16 weight shards contain all 1,557 active model tensors. `weights_manifest.json` records their hashes.
-
-## Python inference
-
-```python
-import torch
-from transformers import AutoModelForCausalLM
-
-model = AutoModelForCausalLM.from_pretrained(
-    '/path/to/hf_checkpoint',  # or 'organization/model-name'
-    trust_remote_code=True,
-    torch_dtype=torch.bfloat16,
-).to('cuda').eval()
-
-image = model.text_to_image('A red ceramic mug on a wooden table.', seed=42)
-image.save('mug.png')
-
-edited = model.image_edit(image, 'Change the mug to blue.', seed=42)
-edited.save('blue_mug.png')
-
-answer = model.generate('What color is the mug?', image=edited)
-print(answer)
-```
-
-Image inputs accept Pillow images or local file paths. Image methods return Pillow images; `generate` returns text by default. Token IDs can be supplied through `input_ids` for text prompts, and `return_token_ids=True` returns the generated token tensor. The `inference.py` command exposes each task.
-
-## Minimal command-line inference
-
-```bash
-python inference.py /path/to/hf_checkpoint --task t2i --prompt 'A red mug.' --output mug.png
-python inference.py /path/to/hf_checkpoint --task edit --image mug.png --prompt 'Make the mug blue.' --output blue.png
-python inference.py /path/to/hf_checkpoint --task understand --image blue.png --prompt 'What color is the mug?'
-```
-
-Replace the model argument with the published Hugging Face model ID for remote loading. The standalone script only uses Transformers and this repository's model code.