Instructions to use FluidInference/gliner2-5-base-coreml with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- GLiNER2
How to use FluidInference/gliner2-5-base-coreml with GLiNER2:
from gliner2 import AutoExtractor extractor = AutoExtractor.from_pretrained("FluidInference/gliner2-5-base-coreml") # 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
Download reports/classification-embedding-w8.json from FluidInference/gliner2-5-base-coreml: direct link, hf CLI and curl.
- Browser
- Download file 5.35 kB
-
https://huggingface.co/FluidInference/gliner2-5-base-coreml/resolve/main/reports/classification-embedding-w8.json
- Command line
-
hf download hf://FluidInference/gliner2-5-base-coreml/reports/classification-embedding-w8.json
-
curl -L -o classification-embedding-w8.json https://huggingface.co/FluidInference/gliner2-5-base-coreml/resolve/main/reports/classification-embedding-w8.json
5.35 kB
| { | |
| "source_revision": "1a8bc24e00dc7300b9017c81d63e3dcdabb26596", | |
| "shape": "L128/K8 classification", | |
| "candidate_package": "gliner2_base_classification_embedding_w8_L128_K8.mlpackage", | |
| "weight_sha256": "037f91cb176d31a38bc1795272d99c47531f3ac235b6f4533bab0df9ae4de327", | |
| "compression": { | |
| "source": "build/gliner2_base_classification_fp16_L128_K8.mlpackage", | |
| "output": "build/gliner2_base_classification_embedding_w8_L128_K8.mlpackage", | |
| "method": "embedding", | |
| "granularity": "per_channel", | |
| "selected_weights": [ | |
| "encoder_embeddings_word_embeddings_weight_to_fp16" | |
| ], | |
| "source_bytes": 388981604, | |
| "output_bytes": 291053994, | |
| "compression_seconds": 5.819930917001329 | |
| }, | |
| "paired_first_manifest_all": { | |
| "reference": "build/gliner2_base_classification_fp16_L128_K8.mlpackage", | |
| "candidate": "build/gliner2_base_classification_embedding_w8_L128_K8.mlpackage", | |
| "manifest": "../../gliner2-small/coreml/fixtures/optimization-selected20.jsonl", | |
| "compute_units": "all", | |
| "processor": "arm", | |
| "machine": "arm64", | |
| "macos": "27.0", | |
| "power_audit_after_run": "Now drawing from 'AC Power'\n -InternalBattery-0 (id=35651683)\t50%; charging; 1:25 remaining present: true", | |
| "reference_load_ms": 2044.181875011418, | |
| "candidate_load_ms": 4582.357916980982, | |
| "warmup_calls_per_model": 1, | |
| "timed_order": "alternating reference-first/candidate-first by request", | |
| "checked": 14, | |
| "choice_agreement": 14, | |
| "max_probability_error": 0.00992196798324585, | |
| "probability_error_limit": 0.02, | |
| "reference_p50_ms": 3.334374981932342, | |
| "candidate_p50_ms": 3.261812496930361, | |
| "reference_p95_ms": 9.934750036336482, | |
| "candidate_p95_ms": 5.232541996520013, | |
| "reference_total_p50_ms": 3.6611664691008627, | |
| "candidate_total_p50_ms": 3.6319584760349244 | |
| }, | |
| "paired_first_manifest_cpu_ane": { | |
| "reference": "build/gliner2_base_classification_fp16_L128_K8.mlpackage", | |
| "candidate": "build/gliner2_base_classification_embedding_w8_L128_K8.mlpackage", | |
| "manifest": "../../gliner2-small/coreml/fixtures/optimization-selected20.jsonl", | |
| "compute_units": "cpu-ane", | |
| "processor": "arm", | |
| "machine": "arm64", | |
| "macos": "27.0", | |
| "power_audit_after_run": "Now drawing from 'AC Power'\n -InternalBattery-0 (id=35651683)\t51%; charging; 1:33 remaining present: true", | |
| "reference_load_ms": 3068.8863749965094, | |
| "candidate_load_ms": 5926.175208995119, | |
| "warmup_calls_per_model": 1, | |
| "timed_order": "alternating reference-first/candidate-first by request", | |
| "checked": 14, | |
| "choice_agreement": 14, | |
| "max_probability_error": 0.0068359375, | |
| "probability_error_limit": 0.02, | |
| "reference_p50_ms": 7.578062970424071, | |
| "candidate_p50_ms": 7.721708010649309, | |
| "reference_p95_ms": 8.475541020743549, | |
| "candidate_p95_ms": 9.883625025395304, | |
| "reference_total_p50_ms": 9.168104501441121, | |
| "candidate_total_p50_ms": 9.666354482760653 | |
| }, | |
| "native_selected100": { | |
| "model": "fastino/gliner2.5-base-v1", | |
| "revision": "1a8bc24e00dc7300b9017c81d63e3dcdabb26596", | |
| "package": "build/gliner2_base_classification_embedding_w8_L128_K8.mlpackage", | |
| "selected_manifest": "first eligible rows in source suite order; no gold labels used", | |
| "counts": { | |
| "checked": 100, | |
| "too_many_options": 300, | |
| "too_long": 7, | |
| "duplicate_labels": 0, | |
| "mismatches": 0 | |
| }, | |
| "maximum_confidence_error": 0.013702988624572754, | |
| "mean_confidence_error": 0.001015886664390564, | |
| "model_call_p50_ms": 10.512874985579401, | |
| "model_call_p95_ms": 14.00475000264123, | |
| "failures": [] | |
| }, | |
| "compute_plan_forced_cpu_ane": { | |
| "total_ops": 516, | |
| "ane_ops": 496, | |
| "cpu_ops": 20, | |
| "ane_percent": 96.1, | |
| "reasons": [ | |
| { | |
| "reason": "Unsupported tensor data type: int32", | |
| "count": 17, | |
| "estimated_cpu_runtime_ms": 2.8975, | |
| "op_types": { | |
| "ios17.expand_dims": 5, | |
| "ios17.cast": 5, | |
| "ios17.add": 2, | |
| "select": 2, | |
| "ios17.gather": 1, | |
| "ios17.mul": 1, | |
| "tile": 1 | |
| }, | |
| "ops": [ | |
| "add_0", | |
| "select_0", | |
| "add_0_1", | |
| "select_0_1", | |
| "inputs_embeds_cast_fp16", | |
| "mask_3", | |
| "mask_3_to_fp16", | |
| "var_86", | |
| "extended_attention_mask", | |
| "extended_attention_mask_to_uint16", | |
| "var_88_cast_int16_to_int32", | |
| "var_89", | |
| "attention_mask_1", | |
| "var_272", | |
| "var_2537", | |
| "indices", | |
| "indices_to_int16" | |
| ] | |
| }, | |
| { | |
| "reason": "Unable to resolve operation input \"y\".", | |
| "count": 2, | |
| "estimated_cpu_runtime_ms": 0.002, | |
| "op_types": { | |
| "ios17.greater_equal": 2 | |
| }, | |
| "ops": [ | |
| "greater_equal_0", | |
| "greater_equal_0_1" | |
| ] | |
| }, | |
| { | |
| "reason": "ANE not available for this op", | |
| "count": 1, | |
| "estimated_cpu_runtime_ms": 0, | |
| "op_types": { | |
| "ios16.constexpr_affine_dequantize": 1 | |
| }, | |
| "ops": [ | |
| "encoder_embeddings_word_embeddings_weight_to_fp16_quantized" | |
| ] | |
| } | |
| ] | |
| }, | |
| "scope": "Selected real classification requests only; no Decision Index or 2048 score; extraction packages are separate." | |
| } | |