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Merge pull request #332 from google-research/rajat-dev

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manually download config.json
This commit is contained in:
Rajat Sen
2025-10-30 13:23:28 -07:00
committed by GitHub
parent c43e8f3e66 be91ef8ee3
commit ddfa6cd9d8
1 changed files with 13 additions and 4 deletions
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src/timesfm/timesfm_2p5/timesfm_2p5_torch.py
+11 -2
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@@ -55,10 +55,12 @@ class TimesFM_2p5_200M_torch_module(nn.Module):
# Layers. # Layers.
self.tokenizer = dense.ResidualBlock(self.config.tokenizer) self.tokenizer = dense.ResidualBlock(self.config.tokenizer)
self.stacked_xf = nn.ModuleList([ self.stacked_xf = nn.ModuleList(
[
transformer.Transformer(self.config.stacked_transformers.transformer) transformer.Transformer(self.config.stacked_transformers.transformer)
for _ in range(self.x) for _ in range(self.x)
]) ]
)
self.output_projection_point = dense.ResidualBlock( self.output_projection_point = dense.ResidualBlock(
self.config.output_projection_point self.config.output_projection_point
) )
@@ -287,6 +289,13 @@ class TimesFM_2p5_200M_torch(timesfm_2p5_base.TimesFM_2p5, ModelHubMixin):
""" """
# Create an instance of the model wrapper class. # Create an instance of the model wrapper class.
instance = cls(**model_kwargs) instance = cls(**model_kwargs)
# Download the config file for hf tracking.
_ = hf_hub_download(
repo_id="google/timesfm-2.5-200m-pytorch",
filename="config.json",
force_download=True,
)
print("Downloaded.")
# Determine the path to the model weights. # Determine the path to the model weights.
model_file_path = "" model_file_path = ""