Comments (2)
martinkim0
commented on August 18, 2024
Hi, thank you for your interest in using MRVI. The model is set to be released with v1.2 (the tutorial shows 1.1.3 because the main branch is set to that version), so the only way to install it currently is from the main branch with the following command:
pip install "scvi-tools @ git+https://github.com/scverse/scvi-tools"
Sorry about that! We're still applying some changes to the code prior to a stable release.
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zy-fang
commented on August 18, 2024
Thank you for your reply. It works for me.
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Related Issues (20)
- Exception has occurred: ImportError cannot import name 'REGISTRY_KEYS' from 'scvi' HOT 3
- Trying to run PeakVI model returns mpi4py error HOT 2
- CellAssign tensor size error HOT 3
- Question about the output of scVI and scANVI HOT 2
- Specifying cell types in the new MRVI tool HOT 1
- Discussion thread: New DestVI model that supports Visium HD (single-cell spatial transcriptomics) data - Timeline, releases and alternatives HOT 2
- Error in py_call_impl(callable, call_args$unnamed, call_args$named) HOT 2
- AttributeError: module 'numpy' has no attribute 'str'. HOT 5
- How to modify scANVI to handle continuous cell labels? HOT 1
- solo.predict() should take an argument to return Non-softmax transformed values, and return logits like previous iterations to allow for non-breaking change that was implemented in 1.1.3 HOT 2
- Update release checklist and documentation for new release workflow HOT 1
- scvi-tools 1.2.0 HOT 3
- Autotuning with Ray: DeprecationWarning: The `RunConfig(local_dir)` argument is deprecated. You should set the `RunConfig(storage_path)` instead. HOT 2
- Use explicit configs instead of kwargs
- autotune throws error for ContrastiveVI (and possibly other external modules) HOT 1
- Fix custom dataloader registry
- ModelTuner.fit Returns error: The `RunConfig(local_dir)` argument is deprecated. HOT 8
- Error in model training HOT 2
- Reproducibility issue of MRVI HOT 4
- In Jupyter Notebook on Windows, the kernel keeps crashing when running Model hyperparameter tuning with scVI. HOT 22
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