6 ms·
Here is the link to the blogpost, that actually describe what this is: https://github.com/google-research/timesfm?tab=readme-ov-file https://github.com/google-r
by EmilStenstrom 6mo ago
Here is the link to the blogpost, that actually describe what this is: https://github.com/google-research/timesfm?tab=readme-ov-file https://github.com/google-research/timesfm?tab=readme-ov-fil...
- refulgentis 6mo agoThat takes me to the same content as the submission, a GitHub repo (Chrome on iOS)
- Cyuonut 6mo agoI suppose they tried to link this: https://research.google/blog/a-decoder-only-foundation-model-for-time-series-forecasting/ https://research.google/blog/a-decoder-only-foundation-model...
- rockwotj 6mo agoProbably the better link: https://research.google/blog/a-decoder-only-foundation-model-for-time-series-forecasting/ https://research.google/blog/a-decoder-only-foundation-model...
- akshayshah 6mo agoAnd https://arxiv.org/pdf/2310.10688 https://arxiv.org/pdf/2310.10688 if you want the full paper.
- nels 6mo agoI think you meant to link this page: https://research.google/blog/a-decoder-only-foundation-model-for-time-series-forecasting/ https://research.google/blog/a-decoder-only-foundation-model...
- OliverGuy 6mo agoWish they gave some numbers for total GPU hours to train this model, seems comparatively tiny when compared to LLMs so interested to know how close this is to something trainable by your average hobbyist/university/small lab
- OliverGuy 6mo agoEdit, it looks like the paper does TPUv5e with 16 tensor cores for 2 days for the 200M param model. Claude reckons this is 60 hours on a 8xA100 rig, so very accessibile compared to LLMs for smaller labs