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Missing files and training code needed to reproduce UniAct from this repo #2

@vkgo

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@vkgo

Hi UniAct authors,

Thanks for releasing the code! I’m trying to reproduce the UniAct text2action pipeline (text → motion tokens → decoder → tracking policy → MuJoCo) using this repository, and potentially retrain the T2A model with our own data. From checking the code, I think several key pieces are missing/unclear:

For inference (text2action)

  1. The motion generator checkpoint directory checkpoints/motion-genorator/ only contains configs and model.safetensors.index.json, but is missing the actual weight shards:
    • model-00001-of-00002.safetensors
    • model-00002-of-00002.safetensors
  2. server.py imports from fsq import FSQ, but there is no fsq module in the repo. Could you point to the correct implementation/package?
  3. The checkpoint folder seems to miss tokenizer assets (e.g., vocab.json), so AutoTokenizer.from_pretrained() may fail in offline setups. What exact files should be included for the motion generator checkpoint?

For training (retraining T2A / motion generator)

  1. Lack of training code for:

    • the tracking policy (RL)
    • the FSQ tokenizer/encoder (motion → token labels)
  2. If we want to retrain only the motion generator while keeping decoder.pt + policy.pt unchanged, we need the exact FSQ token labels (or the tokenizer/encoder to generate them) to keep the token space identical.

Could you please provide links or instructions to obtain the missing ckpts/files and (if available) the training code?

Thanks again!

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