Image-to-Text
Transformers
Safetensors
lana_radgen
feature-extraction
medical-ai
radiology
chest-xray
report-generation
segmentation
anatomical-attention
custom_code
Instructions to use manu02/LAnA-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use manu02/LAnA-v2 with Transformers:
# Use a pipeline as a high-level helper # Warning: Pipeline type "image-to-text" is no longer supported in transformers v5. # You must load the model directly (see below) or downgrade to v4.x with: # 'pip install "transformers<5.0.0' from transformers import pipeline pipe = pipeline("image-to-text", model="manu02/LAnA-v2", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("manu02/LAnA-v2", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "architectures": [ | |
| "DINOv3ConvNextModel" | |
| ], | |
| "depths": [ | |
| 3, | |
| 3, | |
| 27, | |
| 3 | |
| ], | |
| "drop_path_rate": 0.0, | |
| "hidden_act": "gelu", | |
| "hidden_sizes": [ | |
| 96, | |
| 192, | |
| 384, | |
| 768 | |
| ], | |
| "image_size": 224, | |
| "initializer_range": 0.02, | |
| "layer_norm_eps": 1e-06, | |
| "layer_scale_init_value": 1e-06, | |
| "model_type": "dinov3_convnext", | |
| "num_channels": 3, | |
| "torch_dtype": "float32", | |
| "transformers_version": "4.56.0.dev0" | |
| } | |