Time Series Forecasting
Transformers
Safetensors
time series
forecasting
pretrained models
foundation models
time series foundation models
time-series
Instructions to use Salesforce/moirai-1.0-R-large with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Salesforce/moirai-1.0-R-large with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Salesforce/moirai-1.0-R-large", dtype="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "attn_dropout_p": 0.0, | |
| "d_model": 1024, | |
| "distr_output": { | |
| "_target_": "uni2ts.distribution.mixture.MixtureOutput", | |
| "components": [ | |
| { | |
| "_target_": "uni2ts.distribution.student_t.StudentTOutput" | |
| }, | |
| { | |
| "_target_": "uni2ts.distribution.normal.NormalFixedScaleOutput", | |
| "scale": 0.001 | |
| }, | |
| { | |
| "_target_": "uni2ts.distribution.negative_binomial.NegativeBinomialOutput" | |
| }, | |
| { | |
| "_target_": "uni2ts.distribution.log_normal.LogNormalOutput" | |
| } | |
| ] | |
| }, | |
| "dropout_p": 0.0, | |
| "max_seq_len": 512, | |
| "num_layers": 24, | |
| "patch_sizes": [ | |
| 8, | |
| 16, | |
| 32, | |
| 64, | |
| 128 | |
| ], | |
| "scaling": true | |
| } |