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 Download macos/classifier.json from mlboydaisuke/GLiNER2.5-Decide-CoreAI: direct link, hf CLI and curl.
- Browser
- Download file 2.46 kB
-
https://huggingface.co/mlboydaisuke/GLiNER2.5-Decide-CoreAI/resolve/main/macos/classifier.json
- Command line
-
hf download hf://mlboydaisuke/GLiNER2.5-Decide-CoreAI/macos/classifier.json
-
curl -L -o classifier.json https://huggingface.co/mlboydaisuke/GLiNER2.5-Decide-CoreAI/resolve/main/macos/classifier.json
2.46 kB
| { | |
| "model": "fastino/GLiNER2.5-Decide", | |
| "revision": "7ee5da4c2415e32259bcdc0b1a7367c32ce8d6f6", | |
| "dtype": "float16", | |
| "MMAX": 32, | |
| "shapes": [ | |
| { | |
| "S": 256, | |
| "bundle": "gliner25-decide_float16_s256_m32.aimodel", | |
| "bytes": 872988957, | |
| "reference": "reference_s256.json" | |
| }, | |
| { | |
| "S": 512, | |
| "bundle": "gliner25-decide_float16_s512_m32.aimodel", | |
| "bytes": 874561440, | |
| "reference": "reference_s512.json" | |
| } | |
| ], | |
| "host_shape_rule": "use the smallest S in `shapes` with len(input_ids) <= S; longer inputs are outside these bundles (gliner2's classify_text_long chunks such text on the host)", | |
| "graph": { | |
| "relative_position": "bucket table baked at export (S fixed); coreai-torch 0.4.1 lowers aten.div.Tensor(int,int) to integer division — logs/diag_div_probe.log" | |
| }, | |
| "inputs": { | |
| "input_ids": [ | |
| "int32", | |
| [ | |
| 1, | |
| "S" | |
| ] | |
| ], | |
| "attention_mask": [ | |
| "int32", | |
| [ | |
| 1, | |
| "S" | |
| ] | |
| ], | |
| "label_idx": [ | |
| "int32", | |
| [ | |
| 1, | |
| 32 | |
| ] | |
| ] | |
| }, | |
| "outputs": { | |
| "logits": [ | |
| "float32", | |
| [ | |
| 1, | |
| 32 | |
| ] | |
| ] | |
| }, | |
| "marker_ids": { | |
| "[MASK]": 128000, | |
| "[SEP_STRUCT]": 128001, | |
| "[SEP_TEXT]": 128002, | |
| "[P]": 128003, | |
| "[C]": 128004, | |
| "[E]": 128005, | |
| "[R]": 128006, | |
| "[L]": 128007, | |
| "[EXAMPLE]": 128008, | |
| "[OUTPUT]": 128009, | |
| "[DESCRIPTION]": 128010 | |
| }, | |
| "pad": { | |
| "input_ids": 0, | |
| "attention_mask": "1 for real tokens, 0 for padding", | |
| "label_idx": "unused slots repeat the first [L] position (host never reads them)" | |
| }, | |
| "label_idx": "the [L] marker positions of every task, concatenated in task order; the host keeps each task's slice", | |
| "layout": "( [P] <task>[: <prompt>][ [DESCRIPTION] <label>: <desc>]* ( [L] <label> [L] <label> ... ) ) [SEP_STRUCT] ( ... ) [SEP_TEXT] <text words>; every piece tokenized with tokenizer.tokenize(piece) on its own, no CLS/SEP", | |
| "text": "append '.' unless the text ends with . ! ? (empty -> '.'); split with gliner2 WhitespaceTokenSplitter regex (URL | email | @handle | \\w+(?:[-_]\\w+)* | \\S, IGNORECASE); lowercase the word values only; schema strings keep their case", | |
| "decision": { | |
| "single_label": "softmax over the task's logits, argmax", | |
| "multi_label": "sigmoid, every label with prob >= cls_threshold; none -> argmax", | |
| "cls_threshold_default": 0.5, | |
| "temperature": 1.0 | |
| } | |
| } |