timm is missing, a model name is unknown, or weights will not download
A node imports the library, chooses an implementation and may then obtain pretrained weights. Determine which stage failed instead of treating every message as a missing package.
Scope and symptoms
A node imports the library, chooses an implementation and may then obtain pretrained weights. Determine which stage failed instead of treating every message as a missing package.
Search fragments; wording and context vary:
No module named 'timm'
Unknown model
Source-supported context
The official timm installation guide describes installing the library in a Python environment. That installation check is separate from a consuming node's model implementation, pretrained configuration and resource access. V04-TIMM
Distinguish these cases
1. timm is absent from the intended environment or another dependency interrupts its import.
2. Import succeeds but the model name or API expected by the node does not match the installed version.
3. The implementation exists and a pretrained resource fails to download, authenticate or load.
Suggested diagnostic sequence
This sequence is editorial guidance, not a diagnosis of your machine.
1. Record the actual timm, Torch, torchvision and node versions and read the node's dependency declarations. A successful import in another terminal is not evidence about this process.
2. Install a genuinely missing dependency according to the node's requirements. For an unknown model, check its registered name and version rather than substituting a weight filename.
3. If execution reaches pretrained-weight loading, identify the configured repository, revision and file. Investigate access or integrity separately from library installation.
4. In a recoverable environment copy, test minimal model construction, then matching weights and a small input. Compare the versions before replacing a working environment.
Completion checks
The intended implementation is created, compatible weights load and the node completes a minimal forward operation. Listing a model name does not establish that its weights are available.
Limits and cautions
Avoid globally upgrading timm for one node; another consumer may declare a different constraint. A weight substitution needs compatibility evidence rather than a similar filename.
Source review: 2026-09-22. No installation, GPU inference or user-environment repair was executed.
Original sources
- timm installation documentation · 2026-09-22
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Sources & references
Source-based editorial draft; no runtime verification. Version observations are scoped, and unknown wrapper identity is explicit.
01timm installation documentationSource checked: 2026-09-22