Instructions to use TuKoResearch/AuriStream1B_40Pred_BabyView_200k with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use TuKoResearch/AuriStream1B_40Pred_BabyView_200k with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="TuKoResearch/AuriStream1B_40Pred_BabyView_200k", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("TuKoResearch/AuriStream1B_40Pred_BabyView_200k", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
AuriStream1B_40Pred_BabyView_200k
AuriStream 1B (48 layers, d=1280, 16 heads, 40 future-prediction heads) trained for 200k steps on
BabyView audio, tokenized with the 5 ms / 8192-code WavCoch tokenizer
TuKoResearch/WavCochCausalV8192-5ms-babyview.
Inputs must be codes from that tokenizer.
Source run: AuriStream1B_40Pred_BabyView5ms8k_64pod_wd020_do005 (weight decay 0.20, dropout 0.05), checkpoint model_00200000.pt.
from transformers import AutoModel
model = AutoModel.from_pretrained("TuKoResearch/AuriStream1B_40Pred_BabyView_200k", trust_remote_code=True).eval()
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