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**Introduction or background of this discussion**:
OSPP project: "Real-Time IoT Perception Systems Based on Edge-Cloud Collaboration with Large Foundation Models"
**Contents of this discussion…
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Another foundation model we could interface is LagLLama: https://github.com/time-series-foundation-models/lag-llama
While the weights are hosted on HuggingFace, I suppose that they are not usable w…
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Hello,
Thank you for your contributions. I tried to run the UniTS_pretrain_x128.sh script, but after a while, the outputs appeared to be nan, and the corresponding loss value also changed to nan. But…
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Why repeat here? The results generated after repeat (i.e. the parameters of the distribution) should be the same, right? What is the significance of this?
https://github.com/time-series-foundation-…
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Hi,
I am trying to test Lagllama on a prediction task. the dataset i feed is what i use for context. then using that context, i want it to make predictions. however, the first step of the predictions…
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Hi, thank you for your contribution. I have been trying to fine-tune your model in a univariate time series forecasting task with C-MAPSS turbine datasets, the goal is to learn the trajectory pattern …
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Hi lag-llama team,
Thank you for developing this project, it's a highly valuable resource.
I wasn't able to find the lag-llama package on PyPI, which makes it a bit challenging to integrate into …
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Hi! Do you support exogeneous variables for zero-shot predictions and training from scratch? As I see gluonts supports it like static and dynamic features but not sure this works for lag-llama too
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## About
At [^1][^2], we shared a few notes about time series anomaly detection, and forecasting/prediction. Other than using traditional statistics-based time series forecasting methods like [Holt…
amotl updated
4 months ago
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Hello, thank you very much for providing such an excellent idea and implementation. However, the performance of my anomaly detection run has not reached the level stated in your paper. Could you pleas…