litert-community/GLiFormer-Large-NER-LiteRT
token-classification model by litert-community
From the publisher
Model card & documentation
Source previewRead the publisher’s intended use, setup instructions, evaluations and limitations. The original model card is the source of truth.
Run the entity-extraction path of knowledgator/gliformer-large-v1 (575.6M parameters, Apache-2.0) on a phone with Google LiteRT. The official weights were converted with LiteRT Torch; nothing in the math was approximated. The validated Android configuration is LiteRT 2.2.0 on a Samsung Galaxy S26 (SM-S942Q, SM8850, Android 16) with explicit GPU FP32 computation. On 70 English inputs the extracted spans match the official gliformer fp32 CPU implementation exactly (micro-F1 1.000 by label and character offsets) with every shipped file. Other Android GPU families and lower-memory phones have not been validated here. The image is a rendering of the actual output of gliformerlargeners128wfp16.tflite through LiteRT CompiledModel for the sentence in assets/herooutput.json (fictional names). The scores are the values the model returned; it is not a screenshot. One host API, three encoded-window sizes. The host runtime picks the smallest window that fits the text; you call one function and never chunk below the 512-token window.…
Read the full model card ↗ · Preview checked 2026-09-26T08:19:44.831Z
Inside the original model card — Document outline
- GLiFormer Large v1 (NER) for LiteRT — one call, three windows
- What you get
- Minimal usage
- Python — complete pipeline, desktop CPU
- Kotlin — Android GPU with explicit FP32 (s128 graph)
- Host contract
- Measured quality and performance
- Provenance, conversion and license
Headings are captured from the source. Links open the publisher’s document, not a locally hosted copy.
Documentation belongs to its respective authors. Reported project/model license: apache-2.0. A listing is not a grant of reuse or training rights. Confirm the document’s own terms at the source.
Model overview
litert-community/GLiFormer-Large-NER-LiteRT is a token-classification model repository published by litert-community on Hugging Face. The source reports the litert library.
This page summarizes Hub metadata. For intended use, training data, evaluation results and limitations, consult the original model card.
Model facts
- Task
- token-classification
- Library
- litert
- Recent downloads (30 days)
- 0
- Cumulative likes
- 0
- Hugging Face trending score
- 0
- Reported safetensors parameters
- Not reported
- Architecture
- Not reported
- License
- apache-2.0
- Access
- Not gated by Hugging Face
- Created
- 2026-09-26T06:24:28.000Z
- Last modified
- 2026-09-26T06:36:55.000Z
Compatibility and lineage
Reported languages: en
Reported base models: knowledgator/gliformer-large-v1
Parameter count is not a RAM/VRAM requirement. Check precision, quantization, context length and runtime compatibility in the model card; no hardware or API-cost claim is inferred here.
Use and evaluate
Check license terms and access requirements first. Review the model card’s documented loading instructions, evaluations and safety limitations. Benchmark scores are not imported by this directory, and popularity is not an accuracy ranking.
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Source and freshness
Source: Hugging Face Hub. Metadata observed 2026-09-26T06:37:45.751Z. Daily imports are snapshots, not real-time monitoring.
Popularity and source listings do not establish security, suitability, licensing rights or benchmark performance.
Related models
knowledgator/gliformer-large-v1