Text Classification
GLiNER
English
coreai
coreai-aimodel
core-ai
coreaikit
apple
on-device
zero-shot-classification
deberta
typed-decisions
Instructions to use mlboydaisuke/GLiNER2.5-Decide-CoreAI with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- GLiNER
How to use mlboydaisuke/GLiNER2.5-Decide-CoreAI with GLiNER:
from gliner import GLiNER model = GLiNER.from_pretrained("mlboydaisuke/GLiNER2.5-Decide-CoreAI") - Notebooks
- Google Colab
- Kaggle
GLiNER2.5-Decide on Core AI: fp16 graphs S=256/512 (macos JIT, ios h19p AOT), tokenizer, classifier.json, gate fixtures, LICENSE/NOTICE
7464c91 verified | { | |
| "model": "fastino/GLiNER2.5-Decide", | |
| "revision": "7ee5da4c2415e32259bcdc0b1a7367c32ce8d6f6", | |
| "S": 256, | |
| "MMAX": 32, | |
| "case_id": "fd/screen_tags/017", | |
| "selection": "longest-distance range first (S/2 < seq_len <= S), then multi-label, most tasks, longest", | |
| "seq_len": 249, | |
| "text": "[blurb]\nIn this brisk near-future feature, I introduce myself as Nera Vale, the last independent outage auditor in a city where the civic forecast engine assigns every worker a probable mistake. My route begins at the municipal prediction exchange, where I enter the sealed district of Stack Nine to recover a stolen human override before the system schedules an entire neighborhood for evacuation. The local signal crews—known as the Patchers—treat outsiders as corrupted data, and their slang of drift, bleed, and ghost load takes me days to decode. I travel alone through maintenance shafts, rooftop relay farms, and a midnight market held inside an idle data center, trading favors for fragments of the override. There are chase scenes, improvised escapes, and a few sharp comic reversals when the Patchers’ arrogant dispatcher keeps misreading my risk score. Yet the mission turns personal as I learn the forecast engine predicted my arrival years ago. I have one night to reach the central tower, expose the model’s hidden objective, and give the city a choice its algorithms cannot calculate.", | |
| "tasks": { | |
| "genres": { | |
| "labels": [ | |
| "comedy", | |
| "drama", | |
| "action", | |
| "documentary", | |
| "horror", | |
| "romance", | |
| "sci_fi", | |
| "kids" | |
| ], | |
| "multi_label": true | |
| }, | |
| "format": { | |
| "labels": [ | |
| "film", | |
| "series" | |
| ], | |
| "multi_label": false | |
| } | |
| }, | |
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| "task_slices": [ | |
| { | |
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| }, | |
| { | |
| "task": "format", | |
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| ], | |
| "oracle_fp32": [ | |
| { | |
| "task": "genres", | |
| "labels": [ | |
| "comedy", | |
| "drama", | |
| "action", | |
| "documentary", | |
| "horror", | |
| "romance", | |
| "sci_fi", | |
| "kids" | |
| ], | |
| "multi_label": true, | |
| "cls_threshold": 0.5, | |
| "logits": [ | |
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| "probs": [ | |
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| "decision": [ | |
| "comedy", | |
| "action", | |
| "sci_fi" | |
| ] | |
| }, | |
| { | |
| "task": "format", | |
| "labels": [ | |
| "film", | |
| "series" | |
| ], | |
| "multi_label": false, | |
| "cls_threshold": 0.5, | |
| "logits": [ | |
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| "probs": [ | |
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| "decision": "film" | |
| } | |
| ] | |
| } |