metadata
license: other
license_name: adobe-research-license
license_link: https://github.com/adobe-research/speaker-identification/blob/main/LICENSE.md
library_name: pytorch
tags:
- speaker-identification
- quantization
- int8
- roberta
- mediasum
Joint SpeakerID INT8 (weight-only)
INT8 weight-only quantisation of the Joint Speaker Identifier from adobe-research/speaker-identification (Interspeech 2024).
Joint INT8 — 78.87 / 0.00 / 63.28 / 67.60 / 18.34 / 472 MB
| Metric | Value |
|---|---|
| Precision | 78.87 |
| Δ vs FP32 | 0.00 |
| F1 | 63.28 |
| Accuracy | 67.60 |
| Throughput | 18.34 examples/s (Apple M3 Pro, MPS, batch 2) |
| In-memory size | 472 MB (FP32: 1633 MB) |
Same precision, F1, and accuracy as the FP32 Joint baseline at about 3.5× smaller weights.
Code and eval tables: HugoMarchant/speaker-identification-quantisation.
Files
model.pt— quantised bundle (scheme=int8_weight, group size 64)config.json— metrics and load metadata
Load
from huggingface_hub import hf_hub_download
from device_utils import apply_cuda_shims
apply_cuda_shims()
from model_io import load_quantized_bundle
path = hf_hub_download("hmarchant/speaker-id-joint-int8", "model.pt")
model, config, tokenizer, qcfg, info, device = load_quantized_bundle(path)
Requires the companion GitHub repo (custom JointSpeakerIdentifier + WeightOnlyQuantizedLinear).
License
Derived from Adobe Research Speaker Identification. The Adobe Research License allows non-commercial research use only.