mlfoundations / mlfoundations/task_vectors
Give a pre-trained model that can be loaded directly using the ‘model_weights = torch.load(file_path, map_location='cpu')’
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- Dominant language
- Python
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Description
While trying to load the file using Python’s pickle module, I encountered an _pickle.UnpicklingError, stating that persistent IDs in protocol 0 must be ASCII strings. Here is the exact error message:
_pickle.UnpicklingError: persistent IDs in protocol 0 must be ASCII strings
I attempted to resolve the issue by employing various methods, including utilizing the persistent_load parameter with pickle.Unpickler and trying to load the file in different environments, but unfortunately, all efforts have been in vain.
Request for Assistance:
Given the circumstances, I was hoping you could provide some insights or guidance on the following points:
Creation Environment: Could you share details about the environment in which the file was created, including the Python and PyTorch versions used?
Persistent IDs: Any information or context regarding the persistent IDs encountered in the file would be immensely helpful.
Loading Method: If there is a specific method or procedure to correctly load the file, could you please share it with me?
Additional Details: Any other details or specifications about the file that you think might assist in resolving the issue would be greatly appreciated.
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First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
Start by reviewing issue #9 and reproducing the reported torch.load and pickle errors with the available model file. Check the repository's model artifacts and loading instructions, then document the creation environment and provide a directly loadable pre-trained model or a confirmed loading procedure.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python, pytorch
- Domain
- machine-learning
- Issue type
- Feature
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 25/100