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/benchmark-coreml.json from FluidInference/laya-coreml: direct link, hf CLI and curl.
- Browser
- Download file 5.01 kB
-
https://huggingface.co/FluidInference/laya-coreml/resolve/b4c348734c44425a2cad726ea1e2c46dae5f96f5/reports/benchmark-coreml.json
- Command line
-
hf download hf://FluidInference/laya-coreml@b4c348734c44425a2cad726ea1e2c46dae5f96f5/reports/benchmark-coreml.json
-
curl -L -o benchmark-coreml.json https://huggingface.co/FluidInference/laya-coreml/resolve/b4c348734c44425a2cad726ea1e2c46dae5f96f5/reports/benchmark-coreml.json
5.01 kB
| { | |
| "chip" : "Apple M5 Pro", | |
| "elapsed_s" : 22.913529992103577, | |
| "latency_ms" : { | |
| "p50" : 5.2010420000000002, | |
| "p95" : 17.967292 | |
| }, | |
| "lengths" : [ | |
| 128, | |
| 256, | |
| 512, | |
| 1024 | |
| ], | |
| "load_s" : 2.2602130174636841, | |
| "questions" : 3899, | |
| "suites" : { | |
| "app.email_spam" : { | |
| "accuracy" : 0.99250000000000005, | |
| "buckets" : { | |
| "L128" : 98, | |
| "L256" : 117, | |
| "L512" : 93, | |
| "L1024" : 92 | |
| }, | |
| "dropped" : 0, | |
| "latency_ms" : { | |
| "p50" : 5.8082500000000001, | |
| "p95" : 18.628333000000001 | |
| }, | |
| "max_probability_delta_vs_reference" : 0.0070431232452392578, | |
| "n" : 400, | |
| "reference_argmax_agreement" : 1, | |
| "reference_compared" : 400, | |
| "state_truncated" : 9 | |
| }, | |
| "app.guardrails_jailbreak" : { | |
| "accuracy" : 0.80500000000000005, | |
| "buckets" : { | |
| "L128" : 285, | |
| "L256" : 59, | |
| "L512" : 53, | |
| "L1024" : 3 | |
| }, | |
| "dropped" : 0, | |
| "latency_ms" : { | |
| "p50" : 3.8389169999999999, | |
| "p95" : 9.5504999999999995 | |
| }, | |
| "max_probability_delta_vs_reference" : 0.80200904607772827, | |
| "n" : 400, | |
| "reference_argmax_agreement" : 0.995, | |
| "reference_compared" : 400, | |
| "state_truncated" : 0 | |
| }, | |
| "app.model_routing_domain" : { | |
| "accuracy" : 0.44110275689223055, | |
| "buckets" : { | |
| "L128" : 137, | |
| "L256" : 261, | |
| "L512" : 1 | |
| }, | |
| "dropped" : 0, | |
| "latency_ms" : { | |
| "p50" : 5.2591669999999997, | |
| "p95" : 5.8784999999999998 | |
| }, | |
| "max_probability_delta_vs_reference" : 0.027976274490356445, | |
| "n" : 399, | |
| "reference_argmax_agreement" : 1, | |
| "reference_compared" : 399, | |
| "state_truncated" : 0 | |
| }, | |
| "app.moderation_toxicity" : { | |
| "accuracy" : 0.53500000000000003, | |
| "buckets" : { | |
| "L128" : 306, | |
| "L256" : 54, | |
| "L512" : 37, | |
| "L1024" : 3 | |
| }, | |
| "dropped" : 0, | |
| "latency_ms" : { | |
| "p50" : 3.8188749999999998, | |
| "p95" : 9.387041 | |
| }, | |
| "max_probability_delta_vs_reference" : 0.0043558478355407715, | |
| "n" : 400, | |
| "reference_argmax_agreement" : 1, | |
| "reference_compared" : 400, | |
| "state_truncated" : 0 | |
| }, | |
| "app.phishing" : { | |
| "accuracy" : 0.99250000000000005, | |
| "buckets" : { | |
| "L128" : 76, | |
| "L256" : 111, | |
| "L512" : 104, | |
| "L1024" : 109 | |
| }, | |
| "dropped" : 0, | |
| "latency_ms" : { | |
| "p50" : 9.0027089999999994, | |
| "p95" : 19.462250000000001 | |
| }, | |
| "max_probability_delta_vs_reference" : 0.003923460841178894, | |
| "n" : 400, | |
| "reference_argmax_agreement" : 1, | |
| "reference_compared" : 400, | |
| "state_truncated" : 7 | |
| }, | |
| "app.rag_relevance" : { | |
| "accuracy" : 0.67249999999999999, | |
| "buckets" : { | |
| "L128" : 135, | |
| "L256" : 262, | |
| "L512" : 3 | |
| }, | |
| "dropped" : 0, | |
| "latency_ms" : { | |
| "p50" : 5.3082500000000001, | |
| "p95" : 6.2931670000000004 | |
| }, | |
| "max_probability_delta_vs_reference" : 0.0088013410568237305, | |
| "n" : 400, | |
| "reference_argmax_agreement" : 1, | |
| "reference_compared" : 400, | |
| "state_truncated" : 0 | |
| }, | |
| "app.support_triage" : { | |
| "accuracy" : 0.54249999999999998, | |
| "buckets" : { | |
| "L256" : 377, | |
| "L512" : 23 | |
| }, | |
| "dropped" : 0, | |
| "latency_ms" : { | |
| "p50" : 5.297625, | |
| "p95" : 8.8684999999999992 | |
| }, | |
| "max_probability_delta_vs_reference" : 0.0048961937427520752, | |
| "n" : 400, | |
| "reference_argmax_agreement" : 0.99750000000000005, | |
| "reference_compared" : 400, | |
| "state_truncated" : 0 | |
| }, | |
| "jev.ag_news" : { | |
| "accuracy" : 0.93500000000000005, | |
| "buckets" : { | |
| "L128" : 368, | |
| "L256" : 32 | |
| }, | |
| "dropped" : 0, | |
| "latency_ms" : { | |
| "p50" : 3.7891249999999999, | |
| "p95" : 6.5880419999999997 | |
| }, | |
| "max_probability_delta_vs_reference" : 0.010490596294403076, | |
| "n" : 400, | |
| "reference_argmax_agreement" : 1, | |
| "reference_compared" : 400, | |
| "state_truncated" : 0 | |
| }, | |
| "jev.emotion" : { | |
| "accuracy" : 0.53749999999999998, | |
| "buckets" : { | |
| "L128" : 400 | |
| }, | |
| "dropped" : 0, | |
| "latency_ms" : { | |
| "p50" : 3.7059579999999999, | |
| "p95" : 3.8140000000000001 | |
| }, | |
| "max_probability_delta_vs_reference" : 0.020582765340805054, | |
| "n" : 400, | |
| "reference_argmax_agreement" : 1, | |
| "reference_compared" : 400, | |
| "state_truncated" : 0 | |
| }, | |
| "massive_intent.en" : { | |
| "accuracy" : 0.65666666666666662, | |
| "buckets" : { | |
| "L256" : 300 | |
| }, | |
| "dropped" : 0, | |
| "latency_ms" : { | |
| "p50" : 5.2149999999999999, | |
| "p95" : 5.4784579999999998 | |
| }, | |
| "max_probability_delta_vs_reference" : 0.019814342260360718, | |
| "n" : 300, | |
| "reference_argmax_agreement" : 1, | |
| "reference_compared" : 300, | |
| "state_truncated" : 0 | |
| } | |
| } | |
| } |