Instructions to use spybyscript/gliner25-base-litert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- LiteRT
How to use spybyscript/gliner25-base-litert with LiteRT:
# No code snippets available yet for this library. # To use this model, check the repository files and the library's documentation. # Want to help? PRs adding snippets are welcome at: # https://github.com/huggingface/huggingface.js
- GLiNER2
How to use spybyscript/gliner25-base-litert with GLiNER2:
from gliner2 import AutoExtractor extractor = AutoExtractor.from_pretrained("spybyscript/gliner25-base-litert") # 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
Every trained head: explicit spans, relations and records; reference runtime; phone results
ff95cf8 verified Download validation-full.json from spybyscript/gliner25-base-litert: direct link, hf CLI and curl.
- Browser
- Download file 4.24 kB
-
https://huggingface.co/spybyscript/gliner25-base-litert/resolve/main/validation-full.json
- Command line
-
hf download hf://spybyscript/gliner25-base-litert/validation-full.json
-
curl -L -o validation-full.json https://huggingface.co/spybyscript/gliner25-base-litert/resolve/main/validation-full.json
4.24 kB
| { | |
| "about": "Every call type against gliner2 2.0.0 with the original weights (runtime/verify_parity.py): LiteRT 2.2.0 on the CPU, wfp16 encoder.", | |
| "source": "fastino/gliner2.5-base-v1@1a8bc24e00dc7300b9017c81d63e3dcdabb26596", | |
| "corpus": { | |
| "file": "runtime/parity_corpus.json", | |
| "requests": 296, | |
| "identical": 296, | |
| "byCallType": { | |
| "entities": { | |
| "calls": 40, | |
| "refused": 0, | |
| "matched": 40, | |
| "items": 148, | |
| "minSpanF1": 1.0, | |
| "maxConfidenceDifference": 0.000228 | |
| }, | |
| "entities_single": { | |
| "calls": 8, | |
| "refused": 0, | |
| "matched": 8, | |
| "items": 16, | |
| "minSpanF1": 1.0, | |
| "maxConfidenceDifference": 5e-06 | |
| }, | |
| "relations_work": { | |
| "calls": 24, | |
| "refused": 0, | |
| "matched": 24, | |
| "items": 62, | |
| "minSpanF1": 1.0, | |
| "maxConfidenceDifference": 0.000883 | |
| }, | |
| "record_natural": { | |
| "calls": 16, | |
| "refused": 0, | |
| "matched": 16, | |
| "items": 28, | |
| "minSpanF1": 1.0, | |
| "maxConfidenceDifference": 0.00013 | |
| }, | |
| "record_latent": { | |
| "calls": 24, | |
| "refused": 0, | |
| "matched": 24, | |
| "items": 429, | |
| "minSpanF1": 1.0, | |
| "maxConfidenceDifference": 0.000641 | |
| }, | |
| "attributes": { | |
| "calls": 16, | |
| "refused": 0, | |
| "matched": 16, | |
| "items": 31, | |
| "minSpanF1": 1.0, | |
| "maxConfidenceDifference": 0.000298 | |
| }, | |
| "classification_topic": { | |
| "calls": 40, | |
| "refused": 0, | |
| "matched": 40, | |
| "items": 40, | |
| "minSpanF1": 1.0, | |
| "maxConfidenceDifference": 0.001305 | |
| }, | |
| "mixed": { | |
| "calls": 16, | |
| "refused": 0, | |
| "matched": 16, | |
| "items": 68, | |
| "minSpanF1": 1.0, | |
| "maxConfidenceDifference": 0.001358 | |
| }, | |
| "relations_family": { | |
| "calls": 8, | |
| "refused": 0, | |
| "matched": 8, | |
| "items": 15, | |
| "minSpanF1": 1.0, | |
| "maxConfidenceDifference": 0.00033 | |
| }, | |
| "classification_described": { | |
| "calls": 24, | |
| "refused": 0, | |
| "matched": 24, | |
| "items": 24, | |
| "minSpanF1": 1.0, | |
| "maxConfidenceDifference": 0.001187 | |
| }, | |
| "record_anchorless": { | |
| "calls": 8, | |
| "refused": 0, | |
| "matched": 8, | |
| "items": 2, | |
| "minSpanF1": 1.0, | |
| "maxConfidenceDifference": 0.000258 | |
| }, | |
| "structure_event": { | |
| "calls": 24, | |
| "refused": 0, | |
| "matched": 24, | |
| "items": 45, | |
| "minSpanF1": 1.0, | |
| "maxConfidenceDifference": 0.000897 | |
| }, | |
| "classification_multi": { | |
| "calls": 16, | |
| "refused": 0, | |
| "matched": 16, | |
| "items": 22, | |
| "minSpanF1": 1.0, | |
| "maxConfidenceDifference": 0.000356 | |
| }, | |
| "entities_described": { | |
| "calls": 16, | |
| "refused": 0, | |
| "matched": 16, | |
| "items": 40, | |
| "minSpanF1": 1.0, | |
| "maxConfidenceDifference": 0.000411 | |
| }, | |
| "structure_order": { | |
| "calls": 8, | |
| "refused": 0, | |
| "matched": 8, | |
| "items": 22, | |
| "minSpanF1": 1.0, | |
| "maxConfidenceDifference": 0.001252 | |
| }, | |
| "relations_event": { | |
| "calls": 8, | |
| "refused": 0, | |
| "matched": 8, | |
| "items": 15, | |
| "minSpanF1": 1.0, | |
| "maxConfidenceDifference": 0.0002 | |
| } | |
| } | |
| }, | |
| "fixtures": { | |
| "about": "FluidInference's eleven verify-full-extraction fixtures", | |
| "identical": 11, | |
| "total": 11, | |
| "rows": [ | |
| { | |
| "case": "entities", | |
| "structureMatch": true, | |
| "maxConfidenceDifference": 1e-06 | |
| }, | |
| { | |
| "case": "entities_multi", | |
| "structureMatch": true, | |
| "maxConfidenceDifference": 3e-06 | |
| }, | |
| { | |
| "case": "relations", | |
| "structureMatch": true, | |
| "maxConfidenceDifference": 2.2e-05 | |
| }, | |
| { | |
| "case": "relations_two", | |
| "structureMatch": true, | |
| "maxConfidenceDifference": 6e-06 | |
| }, | |
| { | |
| "case": "record_natural", | |
| "structureMatch": true, | |
| "maxConfidenceDifference": 0.000134 | |
| }, | |
| { | |
| "case": "record_latent", | |
| "structureMatch": true, | |
| "maxConfidenceDifference": 0.000352 | |
| }, | |
| { | |
| "case": "record_anchorless", | |
| "structureMatch": true, | |
| "maxConfidenceDifference": null | |
| }, | |
| { | |
| "case": "attributes", | |
| "structureMatch": true, | |
| "maxConfidenceDifference": 2.8e-05 | |
| }, | |
| { | |
| "case": "mixed_classification", | |
| "structureMatch": true, | |
| "maxConfidenceDifference": 1e-06 | |
| }, | |
| { | |
| "case": "classification_only", | |
| "structureMatch": true, | |
| "maxConfidenceDifference": 6.4e-05 | |
| }, | |
| { | |
| "case": "enum_choice", | |
| "structureMatch": true, | |
| "maxConfidenceDifference": 0.0 | |
| } | |
| ] | |
| } | |
| } | |