theforecastingcompany
/

t0-alpha

Time Series Forecasting

probabilistic-forecasting

foundation-models

pretrained-models

known-future-covariates

model_hub_mixin

pytorch_model_hub_mixin

Eval Results (legacy)

Model card Files Files and versions

LTMeyer commited on 23 days ago

Commit

6bb6f5e

·

verified ·

1 Parent(s): 9ad661b

Upload README.md with huggingface_hub

Files changed (1) hide show

README.md +3 -3

README.md CHANGED Viewed

@@ -2,7 +2,7 @@
 license: apache-2.0
 pipeline_tag: time-series-forecasting
 library_name: tfc-t0
-thumbnail: https://www.theforecastingcompany.com/images/og.png
 tags:
   - time-series
   - forecasting
@@ -61,7 +61,7 @@ model-index:
 You can use `t0` on [Retrocast](https://app.retrocast.com/), The Forecasting Company's platform for forecasting on your own data and comparing forecasts across open-weight models.
-![t0 forecasting French national electricity demand in Retrocast](assets/enedis_with_holidays.png)
 _`t0` forecasting French national electricity demand in Retrocast. Data: [Enedis open data](https://data.enedis.fr/)._
@@ -95,7 +95,7 @@ Forecasts should be treated as probabilistic estimates, not guarantees.
 | Without covariates                                                | With covariates                                             |
 | ----------------------------------------------------------------- | ----------------------------------------------------------- |
-| ![t0 forecast without covariates](assets/medicam_without_cov.png) | ![t0 forecast with covariates](assets/medicam_with_cov.png) |
 _Data: [Medic'AM](https://www.assurance-maladie.ameli.fr/etudes-et-donnees/medicaments-classe-atc-medicam), monthly drug reimbursements from the French national health insurance._

 license: apache-2.0
 pipeline_tag: time-series-forecasting
 library_name: tfc-t0
+thumbnail: https://www.theforecastingcompany.com/og/default.png
 tags:
   - time-series
   - forecasting
 You can use `t0` on [Retrocast](https://app.retrocast.com/), The Forecasting Company's platform for forecasting on your own data and comparing forecasts across open-weight models.
+![t0 forecasting French national electricity demand in Retrocast](https://raw.githubusercontent.com/theforecastingcompany/tfc-t0/main/assets/enedis_with_holidays.webp)
 _`t0` forecasting French national electricity demand in Retrocast. Data: [Enedis open data](https://data.enedis.fr/)._
 | Without covariates                                                | With covariates                                             |
 | ----------------------------------------------------------------- | ----------------------------------------------------------- |
+| ![t0 forecast without covariates](https://raw.githubusercontent.com/theforecastingcompany/tfc-t0/main/assets/medicam_without_cov.webp) | ![t0 forecast with covariates](https://raw.githubusercontent.com/theforecastingcompany/tfc-t0/main/assets/medicam_with_cov.webp) |
 _Data: [Medic'AM](https://www.assurance-maladie.ameli.fr/etudes-et-donnees/medicaments-classe-atc-medicam), monthly drug reimbursements from the French national health insurance._