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$ python run_training.py --logfile ../logs/intel.log --save_model_dir ../saved_models/intel --data_dir ../data/disease-prediction --intel
Some weights of the model checkpoint at emilyalsentzer/Bio_Cl…
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Dear xgbse-team,
what would be the correct way for ensembling of predictions? Let's say that I have 5 StackedWeibull models and would like to ensemble their predictions on a test dataset. Should I …
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Hi there,
I have a question regarding the `frozen_model.pb`
I trained a fine-tuned model with a pre-trained checkpoint with efficientdet-d0 to make inferences on my own custom dataset. I export…
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```
from pyspark.ml.feature import VectorAssembler
from pyspark.ml.classification import LogisticRegression
from pyspark.ml.evaluation import BinaryClassificationEvaluator
from pyspark.ml.tuning i…
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For the following code:
```
import torch, torchvision
from efficientnet_pytorch import EfficientNet
from tqdm import tqdm
def main(l):
model = EfficientNet.from_pretrained(model_name='ef…
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### Feature request
I have implemented and tested a feature that trains a time series model - ARIMA and serves it using BentoML's custom runner to make predictions.
### Motivation
I believe it woul…
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**Describe the bug**
While following the tutorial '[Creating a custom serving runtime in KServe ModelMesh](https://developer.ibm.com/tutorials/awb-creating-custom-runtimes-in-modelmesh/)' from th…
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"model_path": 'model_data/mobilenet_ssd_weights.h5'
net['predictions'] = concatenate([net['mbox_loc'],
net['mbox_conf'],
net['mbox…
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Hi!
I performed a node classification task using masking on batch mode. It runs correctly. However, I also need to get more metrics of the model by using the classification report of scikit learn (…
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import matplotlib.pyplot as plt
import pandas as pd
from sklearn import linear_model
from sklearn.preprocessing import PolynomialFeatures as PF
from sklearn.ensemble import RandomForestClassifier
…