Instructions to use mircq/GLINER-INT8 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- GLiNER
How to use mircq/GLINER-INT8 with GLiNER:
from gliner import GLiNER model = GLiNER.from_pretrained("mircq/GLINER-INT8") text = "Cristiano Ronaldo dos Santos Aveiro was born on 5 February 1985 in Funchal, Madeira, Portugal." labels = ["person", "date", "location"] entities = model.predict_entities(text, labels) for entity in entities: print(entity["text"], "=>", entity["label"]) - GLiNER2
How to use mircq/GLINER-INT8 with GLiNER2:
from gliner2 import AutoExtractor extractor = AutoExtractor.from_pretrained("mircq/GLINER-INT8") # 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 tokenizer_config.json from mircq/GLINER-INT8: direct link, hf CLI and curl.
- Browser
- Download file 678 Bytes
-
https://huggingface.co/mircq/GLINER-INT8/resolve/main/tokenizer_config.json
- Command line
-
hf download hf://mircq/GLINER-INT8/tokenizer_config.json
-
curl -L -o tokenizer_config.json https://huggingface.co/mircq/GLINER-INT8/resolve/main/tokenizer_config.json
678 Bytes
| { | |
| "backend": "tokenizers", | |
| "bos_token": "[CLS]", | |
| "clean_up_tokenization_spaces": false, | |
| "cls_token": "[CLS]", | |
| "do_lower_case": false, | |
| "eos_token": "[SEP]", | |
| "extra_special_tokens": [ | |
| "[SEP_STRUCT]", | |
| "[SEP_TEXT]", | |
| "[P]", | |
| "[C]", | |
| "[E]", | |
| "[R]", | |
| "[L]", | |
| "[EXAMPLE]", | |
| "[OUTPUT]", | |
| "[DESCRIPTION]" | |
| ], | |
| "is_local": false, | |
| "mask_token": "[MASK]", | |
| "model_max_length": 1000000000000000019884624838656, | |
| "model_specific_special_tokens": {}, | |
| "pad_token": "[PAD]", | |
| "sep_token": "[SEP]", | |
| "sp_model_kwargs": {}, | |
| "split_by_punct": false, | |
| "tokenizer_class": "TokenizersBackend", | |
| "unk_token": "[UNK]", | |
| "vocab_type": "spm" | |
| } | |