Instructions to use FluidInference/laya-coreml with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Laya
How to use FluidInference/laya-coreml with Laya:
# 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
- Notebooks
- Google Colab
- Kaggle
Download reports/verification-multilingual-L128-w8.json from FluidInference/laya-coreml: direct link, hf CLI and curl.
- Browser
- Download file 18.2 kB
-
https://huggingface.co/FluidInference/laya-coreml/resolve/de76e2e0eb03d7cbcd76e1324ab80198245120e0/reports/verification-multilingual-L128-w8.json
- Command line
-
hf download hf://FluidInference/laya-coreml@de76e2e0eb03d7cbcd76e1324ab80198245120e0/reports/verification-multilingual-L128-w8.json
-
curl -L -o verification-multilingual-L128-w8.json https://huggingface.co/FluidInference/laya-coreml/resolve/de76e2e0eb03d7cbcd76e1324ab80198245120e0/reports/verification-multilingual-L128-w8.json
18.2 kB
| { | |
| "package": "laya_multilingual_w8_L128_options32.mlpackage", | |
| "package_files_sha256": { | |
| "Data/com.apple.CoreML/model.mlmodel": "4d1358ac20b62ec9aa90d76b3ce22e04f76505d3fbc2242f9ea83a47527f709d", | |
| "Data/com.apple.CoreML/weights/weight.bin": "7c0bf0c97c3dfa524571c349f24241d1499514c90f5bef5bfccceb7c1c3cfee4", | |
| "Manifest.json": "4bdc36727345b7bf6c23248407c45a0d5d466b20170506b5ef9c34273b55a68e" | |
| }, | |
| "source_repo": "convaiinnovations/laya", | |
| "source_revision": "1c5edc17a7acd8701df6fc341c0d179f1c62c982", | |
| "variant": "multilingual", | |
| "length": 128, | |
| "max_options": 32, | |
| "precision": "w8", | |
| "package_bytes": 323530193, | |
| "environment": { | |
| "chip": "Apple M5 Pro", | |
| "os": "27.0", | |
| "python": "3.12.13", | |
| "torch": "2.7.0", | |
| "coremltools": "9.0" | |
| }, | |
| "gates": { | |
| "argmax_agreement": "100%", | |
| "max_probability_error": 0.02, | |
| "max_action_probability_error": 0.02, | |
| "finite": true, | |
| "padding_masked": true | |
| }, | |
| "cases_sha256": "4de4e34309c421913524209b62bb7c8a0a232928bd228ec12e884347ce65eeed", | |
| "runs": { | |
| "ALL": { | |
| "compute_units": "ALL", | |
| "load_seconds": 0.30971424997551367, | |
| "questions": 16, | |
| "argmax_agreements": 16, | |
| "max_probability_error": 0.04169827699661255, | |
| "max_action_probability_error": 0.0, | |
| "latency_ms": { | |
| "p50": 4.134541988605633, | |
| "p95": 4.69923158234451, | |
| "min": 3.8557079969905317, | |
| "max": 5.924416007474065 | |
| }, | |
| "skipped": [], | |
| "rows": [ | |
| { | |
| "case": "tetris_clean", | |
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| "tokens": 80, | |
| "options": 2, | |
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| "coreml_argmax": 0, | |
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| "max_action_probability_error": 0.0, | |
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| "probability_sum": 1.00006103515625, | |
| "median_ms": 4.497124988120049 | |
| }, | |
| { | |
| "case": "tetris_flat", | |
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| "median_ms": 4.317542014177889 | |
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| "median_ms": 4.138145508477464 | |
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| "passed": false | |
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| { | |
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| "finite": true, | |
| "padding_masked": true, | |
| "probability_sum": 0.99969482421875, | |
| "median_ms": 3.908667014911771 | |
| } | |
| ], | |
| "passed": false | |
| } | |
| }, | |
| "passed": false | |
| } | |