smdesai/GLiNER25-Decide-FP16-CoreML

GLiNER2.5-Decide — Core ML (iOS 18+ / macOS 15+)

File	Purpose
GLiNER25-Decide-FP16-CoreML.mlpackage/	Core ML package, FP16 weights and compute (~945 MB), three functions sharing one set of weights
tokenizer.json, tokenizer_config.json, special_tokens_map.json	Checkpoint tokenizer
model-card.md	Upstream model card (fastino/GLiNER2.5-Decide, Apache-2.0)

Source: checkpoint revision bbe10ff77ebb238777c17d3a8ac9260e30929057, classification-only (DeBERTa encoder + classifier). Built with coremltools 9.0 / Torch 2.7.1 from FP16 128/256/512 exports (finite FP16 attention mask), merged into one multifunction package with shared weights.

Interface

Functions context128, context256, context512 (select with MLModelConfiguration.functionName):

• inputs: input_ids int32 [1, L], attention_mask int32 [1, L] (1 = real token, 0 = padding)
• output: logits [1, L], one score per token position. Classification reads the positions of the schema's label markers ([L]).

Choose the smallest function that fits the request and pad to its length. The maximum is 512 tokens. Reject longer requests; do not truncate.

Required: GPU compute units

let configuration = MLModelConfiguration()
configuration.computeUnits = .cpuAndGPU
configuration.functionName = "context256"
let model = try MLModel(contentsOf: compiledURL, configuration: configuration)

Do not use INT8 weights on the GPU: they were nondeterministic and changed decisions. Do not rely on .cpuOnly for this package either: FP16 on CPU changes no decisions but exceeds the strict gate (max 0.012). Xcode compiles the .mlpackage to .mlmodelc when it is bundled in an app; use MLModel.compileModel(at:) otherwise.

Validation (iPhone 17 Pro, iOS 27.2, GPU)

Strict gate: every decision matches the FP32 PyTorch oracle and max probability error ≤ 0.005. Two launches per function, identical results:

Function	Corpus	Max error	Median
context128	75	0.001371	26 ms
context256	86	0.001371	44 ms
context512	95 (9 requests of 296–512 tokens)	0.001371	121–124 ms

Load ≈ 1.7–2.0 s; physical footprint ≤ 0.32 GB (weights are file-mapped). Not yet validated on an iOS 18–26 device or an older GPU.

SHA-256

bc1092e6eb7185c9ff1c3fb8e8659b70b8c12f295fc573c39c197f768c102078  GLiNER25-Decide-FP16-CoreML.mlpackage/Data/com.apple.CoreML/weights/weight.bin
fe39a4ea16cb1d35699d4cc2571f9c4e80692caccdafbb689645be56867f8d9f  GLiNER25-Decide-FP16-CoreML.mlpackage/Data/com.apple.CoreML/model.mlmodel
3ad87d9ffe669147063e70850927dd2da90249e2acc5c8527f1eb65df467bcc8  tokenizer.json