google-research/timesfm
TimesFM (Time Series Foundation Model) is a pretrained time-series foundation model developed by Google Research for time-series forecasting.
Python★ 31,116+342 that day#7 on trending7.95% duplicated
128files
33,186lines
170,591tokens
106clones
2,639duplicated lines (7.95%)
10,769duplicated tokens (6.31%)
By format
| Format | Files | Lines | Clones | Duplicated lines | Duplication |
|---|---|---|---|---|---|
| python | 78 | 21,833 | 55 | 1,172 | 5.37% |
| json | 5 | 6,219 | 49 | 1,446 | 23.25% |
| markdown | 15 | 2,462 | 1 | 6 | 0.24% |
| yaml | 3 | 73 | 1 | 15 | 20.55% |
| bash | 13 | 1,345 | 0 | 0 | 0% |
| text | 4 | 460 | 0 | 0 | 0% |
| csv | 5 | 358 | 0 | 0 | 0% |
| perl | 1 | 168 | 0 | 0 | 0% |
| toml | 2 | 125 | 0 | 0 | 0% |
| mermaid | 1 | 94 | 0 | 0 | 0% |
Largest clones
- 130 lines · 1,056 tokens pythonsrc/timesfm/utils/xreg_lib.py:72–201⇆v1/src/timesfm/xreg_lib.py:56–182
- 165 lines · 777 tokens pythonsrc/timesfm/utils/xreg_lib.py:207–371⇆v1/src/timesfm/xreg_lib.py:190–340
- 88 lines · 626 tokens pythonsrc/timesfm/utils/xreg_lib.py:377–464⇆v1/src/timesfm/xreg_lib.py:355–440
- 28 lines · 265 tokens pythonsrc/timesfm/utils/xreg_lib.py:30–57⇆v1/src/timesfm/xreg_lib.py:25–53
- 31 lines · 224 tokens pythonv1/src/timesfm/timesfm_base.py:314–344⇆v1/src/timesfm/timesfm_torch.py:72–103
- 21 lines · 203 tokens pythonsrc/timesfm/utils/xreg_lib.py:75–95⇆src/timesfm/utils/xreg_lib.py:177–197
- 26 lines · 187 tokens pythonv1/src/timesfm/timesfm_base.py:312–337⇆v1/src/timesfm/timesfm_jax.py:237–262
- 29 lines · 185 tokens pythonsrc/timesfm/timesfm_2p5/timesfm_2p5_flax.py:515–543⇆src/timesfm/timesfm_2p5/timesfm_2p5_torch.py:391–419
- 37 lines · 157 tokens pythonv1/src/adapter/lora_layers.py:103–139⇆v1/src/adapter/lora_layers.py:139–166
- 17 lines · 142 tokens pythonsrc/timesfm/timesfm_2p5/timesfm_2p5_flax.py:99–115⇆src/timesfm/timesfm_2p5/timesfm_2p5_torch.py:42–58
Trending appearances
| Day | Rank | Stars | Files | Lines | Clones | Duplication | Health | Commit |
|---|---|---|---|---|---|---|---|---|
| Sep 5, 2026 | #7 | 31,116 (+342) | 128 | 33,186 | 106 | 7.95% | — | 0df95ae |
| Sep 4, 2026 | #4 | 30,771 (+1,618) | 128 | 33,115 | 105 | 7.95% | — | aa48015 |
| Sep 3, 2026 | #2 | 30,144 (+343) | 128 | 33,115 | 105 | 7.95% | — | aa48015 |
Want this for your own project? Install jscpd and run jscpd .