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awslabs / autogluon

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haystack

deepset-ai / haystack

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Add user feedback buttons to UI to collect domain-specifc training data

tholor
tholor commented Feb 26, 2021

Is your feature request related to a problem? Please describe.
If you work on domain corpora, collecting additional training data to improve your reader or retriever models is very helpful.
For collecting training data, there are two main options:
a) Manual Labelling
b) User feedback for "live predictions"

b) is particularly promising if you don't have enough time or resources for a)

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good first issue type:feature
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transfer-learning-conv-ai

huggingface / transfer-learning-conv-ai

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RuntimeError: shape '[-1, 2, 34]' is invalid for input of size 61710

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jb33k
jb33k commented Jun 4, 2019

I'm playing around with this wonderful code but I'm running into a curious issue when I try to train the model with my own data.

I replicated the personachat_self_original.json file structure and added my own data. I deleted dataset_cache_OpenAIGPTTokenizer file but when I try to train, I get this error:

INFO:train.py:Pad inputs and convert to Tensor
Traceback (most recent call last)
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good first issue

curiousily / Getting-Things-Done-with-Pytorch

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Jupyter Notebook tutorials on solving real-world problems with Machine Learning & Deep Learning using PyTorch. Topics: Face detection with Detectron 2, Time Series anomaly detection with LSTM Autoencoders, Object Detection with YOLO v5, Build your first Neural Network, Time Series forecasting for Coronavirus daily cases, Sentiment Analysis with BERT.

nlp machine-learning tutorial computer-vision deep-learning time-series sentiment-analysis pytorch transformer lstm yolo face-recognition face-detection object-detection transfer-learning bert anomaly-detection time-series-forecasting coronavirus time-series-anomaly-detection
  • Updated Apr 26, 2021
  • Jupyter Notebook

chaoyanghe / Awesome-Federated-Learning

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Federated Learning Library: https://fedml.ai

machine-learning privacy computer-vision semi-supervised-learning transfer-learning wireless-communication distributed-optimization interpretability neural-architecture-search federated-learning continual-learning vertical-federated-learning non-iid decentralized-federated-learning hierarchical-federated-learning adversarial-attack-and-defense communication-efficiency straggler-problem computation-efficiency incentive-mechanism
  • Updated Apr 28, 2021
flow-forecast

AIStream-Peelout / flow-forecast

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