What was used to build the index in RAG?
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161
Machine Learning / AI
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What to do at the end of training?
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160
What is the difference between data parallelism and model parallelism?
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156
How do you output a list of results?
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156
How does ROC-AUC differ from other metrics?
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153
What is sparse attention?
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152
What is the purpose of the anchor in Triplet Loss?
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150
What is the difference between Margin Loss and Triplet Loss?
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149
What is an epoch?
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148
What is n in the context of attention complexity?
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147
How is a reranker trained?
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146
If there are no reference answers, only documents and context — how to evaluate the system and where to get the reference answer?
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146
What types of optimization exist for LLM?
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145
What else besides cross-entropy can be used as a loss function?
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145
What has changed in LLM compared to the original transformer?
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143
What type of attention allows reducing complexity below O(n²)?
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135
What is gradient checkpointing?
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133
What is quantization?
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131
How to evaluate an agent implementing RAG?
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130
What happens if you input a sequence of 10k tokens to a decoder, but the model was trained on 9k?
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128