Feature Extraction
Transformers
Safetensors
English
symtime
time series
forecasting
foundation models
pretrained models
generative models
time series foundation models
custom_code
Instructions to use FlowVortex/SymTime with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use FlowVortex/SymTime with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="FlowVortex/SymTime", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("FlowVortex/SymTime", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
File size: 539 Bytes
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{
"architectures": [
"SymTimeModel"
],
"_name_or_path": "FlowVortex/SymTime",
"auto_map": {
"AutoConfig": "configuration_symtime.SymTimeConfig",
"AutoModel": "model.SymTimeModel"
},
"patch_size": 16,
"stride": 16,
"num_layers": 6,
"d_model": 512,
"d_ff": 2048,
"num_heads": 8,
"norm": "BatchNorm",
"dropout": 0.1,
"act": "gelu",
"pre_norm": false,
"initializer_factor": 0.05,
"model_type": "symtime",
"torch_dtype": "float32",
"transformers_version": "5.5.4"
} |