Feature Extraction
Transformers
Safetensors
Italian
radgraph_it
radiology
information-extraction
named-entity-recognition
relation-extraction
medical
radgraph
custom_code
Instructions to use radgraphIT/Radgraph-IT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use radgraphIT/Radgraph-IT with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="radgraphIT/Radgraph-IT", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("radgraphIT/Radgraph-IT", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "manifest_version": 1, | |
| "package": "radgraphit", | |
| "min_package_version": "0.1.0", | |
| "schema": "radgraph-xl", | |
| "backend": "dygie_v2", | |
| "encoder": { | |
| "model_name": "IVN-RIN/medBIT-r3-plus", | |
| "max_length": 512 | |
| }, | |
| "revision": "v1", | |
| "weights_file": "best.pt", | |
| "files": { | |
| "config.json": { | |
| "sha256": "378f0c083f71662e204c8876b805ba8298f7a056db4b6cc64b95079a0d476d23" | |
| }, | |
| "vocab.json": { | |
| "sha256": "e32c6ab26dad1625dfc3f5fa2bcf91d466ba7cf231da0ab78846eae84ad20f76" | |
| }, | |
| "best.pt": { | |
| "sha256": "987fc75edf3ac78d1a0f05b8260f832c16ccd0cb6d6612432b2c0dbdf00a757a" | |
| } | |
| } | |
| } | |