Instructions to use Reza2kn/visualears-fastconformer-fa32m-streaming-bpe1024 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- NeMo
How to use Reza2kn/visualears-fastconformer-fa32m-streaming-bpe1024 with NeMo:
import nemo.collections.asr as nemo_asr asr_model = nemo_asr.models.ASRModel.from_pretrained("Reza2kn/visualears-fastconformer-fa32m-streaming-bpe1024") transcriptions = asr_model.transcribe(["file.wav"]) - Notebooks
- Google Colab
- Kaggle
VisualEars FastConformer FA32M Streaming BPE1024
Persian/Farsi ASR checkpoint from the VisualEars train32 run.
Benchmark
Run completed: 2026-06-14T22:59:18Z
| Set | N | WER | CER |
|---|---|---|---|
| Gold69 v2 fair | 69 | 31.14% | 13.86% |
| FLEURS fa_ir test | 871 | 17.55% | 6.16% |
Summary JSON: benchmark_results/fa32m_full9669_gold69_fleurs_summary_20260614T225848Z.json
Files
fa32m_streaming_bpe1024_final.nemoβ final NVIDIA NeMo archive.final_stats.jsonβ export metadata from the training box.train32_full.pyβ training script used for the run.benchmark_32m_gold69_fleurs.pyβ benchmark/eval harness.manifest_stats.jsonβ manifest row/hour stats.benchmark_results/fa32m_full9669_gold69_fleurs_summary_20260614T225848Z.jsonβ benchmark summary.benchmark_results/fa32m_full9669_gold69_fleurs_benchmark_20260614T225848Z.logβ benchmark log.
Provenance
- Run directory:
/workspace/train32_runs/fa32m_streaming_bpe1024_full9669_20260614T130932Z - Source artifact:
/workspace/train32_runs/fa32m_streaming_bpe1024_full9669_20260614T130932Z/fa32m_streaming_bpe1024_final.nemo - Base model:
nvidia/stt_en_fastconformer_hybrid_medium_streaming_80ms - Tokenizer dir:
/workspace/train32_bootstrap/tokenizers/fa_bpe_1024 - SHA256 (
fa32m_streaming_bpe1024_final.nemo):034fb2afa19da13db8a120970a7f8d3e696987014cc62684ce50a1382d332448 - Size:
127170560bytes - Uploaded/updated:
2026-06-14T23:00:02Z
Manifest stats
{
"train": {
"rows": 5578135,
"hours": 8862.916194048803
},
"val": {
"rows": 56155,
"hours": 89.6981422569458
},
"total": {
"rows": 5634290,
"hours": 8952.614336305749
}
}
Loading
This is a NeMo .nemo artifact. Example:
import nemo.collections.asr as nemo_asr
model = nemo_asr.models.ASRModel.restore_from("fa32m_streaming_bpe1024_final.nemo")
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