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Oftentimes, one wants to build linear models having ordinal variables as features (e.g. "rate in a scale from 1 to 5 ..."). One might treat these as numerical or categorical, but this loses some infor…
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we found this benchmark here:
https://github.com/diux-dev/cluster/tree/master/pytorch_distributed_benchmark
will be interesting to have a look if we observe similar speed, and code is probably use…
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Env created for testing those models here 881527314fe1b49eef92b50ccd6a9869d48468ef
I suggest we split the tasks into 3. A quick look suggests that cyclic and bifurcation networks are relatively har…
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Hi,
I am new to mixed-effect models. I have a longitudinal phenotype data and every subject has different numbers of longitudinal measurements. All the covariates are not time-dependent. I am wonde…
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When I convert BERT (pytorch model) to onnx format (without any optimizations) and then try to run the "symbolic_shape_infer.py" script with the obtained onnx model as an input argument, I get the fol…
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RLM assumes in general a symmetric distribution otherwise we need to add a term into the estimating equations for Fisher consistency. For the latter case we (will) have special models for specific asy…
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I noticed that a new projector head MLP is added after loading the pre-trained MoCo v3 model. However, the parameters of this newly added component are also set to requires_grad=False.
My question …
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In Lester et al. (2021), they use T5 as the pre-trained model and use LM head to generate answers.
For models like BERT, Roberta explored in this work, we can not use LM head to extract context spans…
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hi, I am training my own model, I want to load pretrain controlnet use "--controlnet_model_name_or_path", but there is an error:
Traceback (most recent call last):
File "train_seesr.py", line …
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Thank you so much for your excellent and inspiring work!!!
I could reproduce the exciting performance using your pre-trained model. However, I failed to reproduce the performances by re-training y…