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AuriStream7BDeep_1Pred_BigAudioDataset_500k-randinit

AuriStream is a speech language model by Greta Tuckute and Klemen Kotar.

This model predicts cochlear tokens from a tokenizer such as WavCochCausalV8192.

Native training step-zero initialization for the 7B-Deep 1-prediction model. This exactly uses origin seed 1110 and historical source commit d4e8241b5b7596323e014395e4670756a0caa70e, matching the start of W&B run dtmvo7ql. The weights are untrained FP32 values produced before XLA/FSDP wrapping.

Model Details

Parameter	Value
Parameters	~7.59B
Layers	96
Hidden Size	2560
Attention Heads	32
Vocab Size	8192
Prediction Steps	1

Usage

from transformers import AutoModel, AutoConfig

# Load with trust_remote_code for custom model
model = AutoModel.from_pretrained(
    "TuKoResearch/AuriStream7BDeep_1Pred_BigAudioDataset_500k-randinit",
    trust_remote_code=True,
)

# Or load config first
config = AutoConfig.from_pretrained("TuKoResearch/AuriStream7BDeep_1Pred_BigAudioDataset_500k-randinit", trust_remote_code=True)

Base Model Code

This checkpoint uses shared model code from TuKoResearch/AuriStream-base.

Tokenizer

This model uses cochlear tokens from WavCochCausalV8192.

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Safetensors

Model size

8B params

Tensor type

F32