language:
- tr
- hi
license: cc-by-nc-4.0
base_model: CohereLabs/tiny-aya-base
base_model_relation: adapter
tags:
- superseded
- checkpoint-artifact
- tinyaya
pipeline_tag: audio-to-audio
pretty_name: TinyAya Stage 2 (superseded run artifact)
TinyAya Stage 2 — superseded run artifact
⚠️ Not a release. Use v0.3 instead.
This repo holds a single intermediate checkpoint pushed automatically by the trainer during an early Stage-2 run. It has no evaluation, no checkpoint suite, and no guarantee about which step it represents.
The released model is
tr-hi-s2st-v0.3, which ships ~89 checkpoints, a full evaluation, and audio samples.
Contents are the standard composite layout — peft_adapter/, projection.pt,
depth_decoder.pt, audio_heads.pt, text_embed.pt, metadata.json. Kept
public for provenance rather than deleted.
Weights are LoRA derivatives of CohereLabs/tiny-aya-base (CC-BY-NC-4.0) and
inherit its non-commercial terms.
Code
| repo | what it does |
|---|---|
model |
Stage-2 training, evaluation harness and TPU launch tooling |
Project
TinyAya Stage 2 — Turkish⇄Hindi speech-to-speech translation with a text inner-monologue: a LoRA-adapted Cohere2 backbone driving a frozen Moshi depth decoder over Mimi codes.
The v0.3 run covered 76,250 steps / 2.07 epochs on a Cloud TPU v6e-16 (best val composite 2.8199 @ step 76,000). Read honestly: the text inner-monologue learns to translate (free-run chrF++ ~25.7 / 25.1), while intelligible audio synthesis remains the frontier (ASR-chrF++ 3.7 / 9.6 against a 92.1 / 86.6 ground-truth-audio ceiling) — bounded by the frozen depth decoder, not by translation understanding.
- Results: v0.3 evaluation report
- Training run: W&B
xzcb60bl· emergence report - Blog: Adapting Moshi for Low-Resource Speech Translation
Compute for the v0.3 run was provided by Google's TPU Research Cloud (TRC).