paris-noah
/

Tabby

Time Series Forecasting

feature-extraction

foundation-model

probabilistic-forecasting

quantile-regression

Model card Files Files and versions

XSF0528 commited on Sep 17

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4da4d58

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verified ·

1 Parent(s): e0f11a0

Update README.md

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@@ -38,7 +38,7 @@ pip install torch transformers einops numpy
 import torch
 from transformers import AutoModel
-model = AutoModel.from_pretrained("<namespace>/Tabby", trust_remote_code=True).eval()
 history = torch.randn(4, 8096).cumsum(-1)      # [B, Tc] — any length; NaN = unobserved
 q = model.predict(history, prediction_length=96)   # [4, 99, 96]

 import torch
 from transformers import AutoModel
+model = AutoModel.from_pretrained("paris-noah/Tabby", trust_remote_code=True).eval()
 history = torch.randn(4, 8096).cumsum(-1)      # [B, Tc] — any length; NaN = unobserved
 q = model.predict(history, prediction_length=96)   # [4, 99, 96]