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Quantization and Swap Memory for GPTQ
Here’s how it works: first, we “quantize” the weights in the neural network that makes up our language model. This means taking all those…
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GPTQ for Llama: 4 bits quantization using GPTQ
Use examples when they help make things clearer. Let me break it down for you. GPTQ stands for “Gradient Pursuit Quantization,” and it’s a…
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PubLayNet Dataset for Document Layout Analysis
These pages have been annotated with both bounding boxes and polygonal segmentations, which means we can see exactly where each word or image is…
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FlaxBartForCausalLMModule: A New Approach to Language Modeling
Now what this actually means. Language models are basically computer programs that can understand and generate human-like text. They work by analyzing patterns in…
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FlaxBartForSequenceClassificationModule: A New Approach to Sequence Classification
Use examples when they help make things clearer. The FlaxBartForSequenceClassificationModule is a modification of the BART (Bidirectional Encoder Representations from Transformers) model, which has…
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FlaxBartDecoderLayerCollection
So how does it work? Well, imagine you have a big ol’ text document and you want to analyze the words inside it. FlaxBartDecoderLayerCollection…