Instructions to use FluidInference/gliner2-5-multi-coreml with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- GLiNER2
How to use FluidInference/gliner2-5-multi-coreml with GLiNER2:
from gliner2 import AutoExtractor extractor = AutoExtractor.from_pretrained("FluidInference/gliner2-5-multi-coreml") # Extract entities text = "Apple CEO Tim Cook announced iPhone 15 in Cupertino yesterday." result = extractor.extract_entities(text, ["company", "person", "product", "location"]) print(result) - Notebooks
- Google Colab
- Kaggle
Download assets.lock.json from FluidInference/gliner2-5-multi-coreml: direct link, hf CLI and curl.
- Browser
- Download file 817 Bytes
-
https://huggingface.co/FluidInference/gliner2-5-multi-coreml/resolve/main/assets.lock.json
- Command line
-
hf download hf://FluidInference/gliner2-5-multi-coreml/assets.lock.json
-
curl -L -o assets.lock.json https://huggingface.co/FluidInference/gliner2-5-multi-coreml/resolve/main/assets.lock.json
817 Bytes
| { | |
| "source": "fastino/gliner2.5-multi-v1", | |
| "revision": "a221b77a8baf4a613b8f8652661d41fa10a5641e", | |
| "files": { | |
| "config.json": { | |
| "size": 3151, | |
| "sha256": "8b59a0f426a65859c89cd1ea850c3529c09aa3be3a6fafd8eddfdd17b1bf0146" | |
| }, | |
| "encoder_config/config.json": { | |
| "size": 857, | |
| "sha256": "fa4f9ef2903b5369ab172333aae4574e6a476511d7465845cf59f8360ee18716" | |
| }, | |
| "model.safetensors": { | |
| "size": 1149461028, | |
| "sha256": "c1ff4ec0bc00031c15530b8f3c33d3677f27949e6a0cb52e1247a6224b6c5395" | |
| }, | |
| "tokenizer.json": { | |
| "size": 16035853, | |
| "sha256": "c62446df87ae18ec98b133f8f84fc449a07cc89bbf8ef192a4cb5f9c53777a7a" | |
| }, | |
| "tokenizer_config.json": { | |
| "size": 645, | |
| "sha256": "0bf3ea0873234bd9bfdd3853c440395009ac6365a925b91654daed5396d655e1" | |
| } | |
| } | |
| } | |