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Bug using "scvi-tools/tabula-sapiens-heart-stereoscope" hugging face scvi model - scvi-tools 1.0.4
Hi!
I followed this tutorial scvi-hugging-face to load pre-trained scvi models and make some predictions/obtain the latent representation.
This is my current environment:
env.yaml
name: base channels:
- conda-forge
- pytorch
- defaults
- nvidia
- bioconda dependencies:
- pyopenssl
- python=3.9
- requests
- pip:
- -r requirements.txt
- numpy
- pytorch::pytorch=2.1=py3.9_cuda12.1*
- torchvision=>0.16
- torchaudio
- biopython
- h5py
- scipy
- scikit-learn
- pandas
- matplotlib
- hdf5plugin
- pyro-ppl
- scanpy
- dill
- umap-learn
- seaborn
- dataframe_image
- xmltodict
- nbconvert
- bioconda::cellxgene
- conda-forge::lightning
- numba
- conda-forge::scvi-tools==1.0.4
- conda-forge::jax[cuda12_pip]
- conda-forge::jaxlib
- conda-forge::huggingface_hub
- conda-forge::leidenalg
requirements.txt
gget cellxgene-census
I decided to start with this example:
from scvi.hub import HubModel
torch.set_float32_matmul_precision('high')
scvi.settings.seed = 0
repository = "scvi-tools/tabula-sapiens-heart-stereoscope"
hubmodel = HubModel.pull_from_huggingface_hub(repository, cache_dir=None, revision="main")
print(hubmodel.model)
However, there was some issue with loading the model due to some attributes inconsistency.
Fetching 3 files: 100%|██████████| 3/3 [00:00<00:00, 11904.36it/s]
INFO Loading model...
Traceback (most recent call last):
File ".../test_scanvi.py", line 163, in <module>
print(hubmodel.model)
File "/home/.../micromamba/lib/python3.9/site-packages/scvi/hub/hub_model.py", line 230, in model
self.load_model()
File "/home/.../micromamba/lib/python3.9/site-packages/scvi/hub/hub_model.py", line 275, in load_model
model_cls = getattr(python_module, model_cls_name)
AttributeError: module 'scvi.model' has no attribute 'RNAStereoscope'
I have been able to run this one:
from scvi.hub import HubModel
torch.set_float32_matmul_precision('high')
scvi.settings.seed = 0
repository = "scvi-tools/heart-cell-atlas-scvi"
hubmodel = HubModel.pull_from_huggingface_hub(repository, cache_dir=None, revision="main")
print(hubmodel.model)
Is this error expected due to an error in my implementation or the hugging face interface is still experimental and some errors are expected?
Thank you in advance for your time!
This indeed an issue on our end, apologies. I'll get this fixed ASAP!