add moirai-1.1 config files

README.md

@@ -7,6 +7,8 @@ Uni2TS also provides tools for fine-tuning, inference, and evaluation for time s
 
 ## 🎉 What's New
 
+* Jun 2024: Released Moirai-1.1-R model weights in [small](https://huggingface.co/Salesforce/moirai-1.1-R-small), [base](https://huggingface.co/Salesforce/moirai-1.1-R-base), and [large](https://huggingface.co/Salesforce/moirai-1.1-R-large).
+
 * May 2024: The Uni2TS paper has been accepted to ICML 2024 as an Oral presentation!
 
 * Mar 2024: Release of Uni2TS library, along with [Moirai-1.0-R](https://huggingface.co/collections/Salesforce/moirai-10-r-models-65c8d3a94c51428c300e0742) and [LOTSA data](https://huggingface.co/datasets/Salesforce/lotsa_data/)!

cli/conf/eval/model/moirai_1.1_R_base.yaml

@@ -0,0 +1,7 @@
+_target_: uni2ts.model.moirai.MoiraiForecast
+module:
+  _target_: uni2ts.model.moirai.MoiraiModule.from_pretrained
+  pretrained_model_name_or_path: Salesforce/moirai-1.1-R-base
+num_samples: 100
+patch_size: ???
+context_length: ???

cli/conf/eval/model/moirai_1.1_R_large.yaml

@@ -0,0 +1,7 @@
+_target_: uni2ts.model.moirai.MoiraiForecast
+module:
+  _target_: uni2ts.model.moirai.MoiraiModule.from_pretrained
+  pretrained_model_name_or_path: Salesforce/moirai-1.1-R-large
+num_samples: 100
+patch_size: ???
+context_length: ???

cli/conf/eval/model/moirai_1.1_R_small.yaml

@@ -0,0 +1,7 @@
+_target_: uni2ts.model.moirai.MoiraiForecast
+module:
+  _target_: uni2ts.model.moirai.MoiraiModule.from_pretrained
+  pretrained_model_name_or_path: Salesforce/moirai-1.1-R-small
+num_samples: 100
+patch_size: ???
+context_length: ???

cli/conf/finetune/model/moirai_1.1_R_base.yaml

@@ -0,0 +1,33 @@
+# load a pretrained checkpoint from huggingface hub
+_target_: uni2ts.model.moirai.MoiraiFinetune
+module:
+  _target_: uni2ts.model.moirai.MoiraiModule.from_pretrained
+  pretrained_model_name_or_path: Salesforce/moirai-1.1-R-base
+module_kwargs:
+  _target_: builtins.dict
+  distr_output:
+    _target_: uni2ts.distribution.MixtureOutput
+    components:
+      - _target_: uni2ts.distribution.StudentTOutput
+      - _target_: uni2ts.distribution.NormalFixedScaleOutput
+      - _target_: uni2ts.distribution.NegativeBinomialOutput
+      - _target_: uni2ts.distribution.LogNormalOutput
+  d_model: 768
+  num_layers: 12
+  patch_sizes: ${as_tuple:[8, 16, 32, 64, 128]}
+  max_seq_len: 512
+  attn_dropout_p: 0.0
+  dropout_p: 0.0
+  scaling: true
+min_patches: 2
+min_mask_ratio: 0.15
+max_mask_ratio: 0.5
+max_dim: 128
+loss_func:
+  _target_: uni2ts.loss.packed.PackedNLLLoss
+lr: 1e-3
+weight_decay: 1e-1
+beta1: 0.9
+beta2: 0.98
+num_training_steps: ${mul:${trainer.max_epochs},${train_dataloader.num_batches_per_epoch}}
+num_warmup_steps: 0

cli/conf/finetune/model/moirai_1.1_R_large.yaml

@@ -0,0 +1,33 @@
+# load a pretrained checkpoint from huggingface hub
+_target_: uni2ts.model.moirai.MoiraiFinetune
+module:
+  _target_: uni2ts.model.moirai.MoiraiModule.from_pretrained
+  pretrained_model_name_or_path: Salesforce/moirai-1.1-R-large
+module_kwargs:
+  _target_: builtins.dict
+  distr_output:
+    _target_: uni2ts.distribution.MixtureOutput
+    components:
+      - _target_: uni2ts.distribution.StudentTOutput
+      - _target_: uni2ts.distribution.NormalFixedScaleOutput
+      - _target_: uni2ts.distribution.NegativeBinomialOutput
+      - _target_: uni2ts.distribution.LogNormalOutput
+  d_model: 1024
+  num_layers: 24
+  patch_sizes: ${as_tuple:[8, 16, 32, 64, 128]}
+  max_seq_len: 512
+  attn_dropout_p: 0.0
+  dropout_p: 0.0
+  scaling: true
+min_patches: 2
+min_mask_ratio: 0.15
+max_mask_ratio: 0.5
+max_dim: 128
+loss_func:
+  _target_: uni2ts.loss.packed.PackedNLLLoss
+lr: 1e-3
+weight_decay: 1e-1
+beta1: 0.9
+beta2: 0.98
+num_training_steps: ${mul:${trainer.max_epochs},${train_dataloader.num_batches_per_epoch}}
+num_warmup_steps: 0

cli/conf/finetune/model/moirai_1.1_R_small.yaml

@@ -0,0 +1,37 @@
+# load a pretrained checkpoint from huggingface hub
+_target_: uni2ts.model.moirai.MoiraiFinetune
+module:
+  _target_: uni2ts.model.moirai.MoiraiModule.from_pretrained
+  pretrained_model_name_or_path: Salesforce/moirai-1.1-R-small
+module_kwargs:
+  _target_: builtins.dict
+  distr_output:
+    _target_: uni2ts.distribution.MixtureOutput
+    components:
+      - _target_: uni2ts.distribution.StudentTOutput
+      - _target_: uni2ts.distribution.NormalFixedScaleOutput
+      - _target_: uni2ts.distribution.NegativeBinomialOutput
+      - _target_: uni2ts.distribution.LogNormalOutput
+  d_model: 384
+  num_layers: 6
+  patch_sizes: ${as_tuple:[8, 16, 32, 64, 128]}
+  max_seq_len: 512
+  attn_dropout_p: 0.0
+  dropout_p: 0.0
+  scaling: true
+min_patches: 2
+min_mask_ratio: 0.15
+max_mask_ratio: 0.5
+max_dim: 128
+loss_func:
+  _target_: uni2ts.loss.packed.PackedNLLLoss
+val_metric:
+  - _target_: uni2ts.loss.packed.PackedMSELoss
+  - _target_: uni2ts.loss.packed.PackedNRMSELoss
+    normalize: absolute_target_squared
+lr: 1e-3
+weight_decay: 1e-1
+beta1: 0.9
+beta2: 0.98
+num_training_steps: ${mul:${trainer.max_epochs},${train_dataloader.num_batches_per_epoch}}
+num_warmup_steps: 0