Enhances Llama decoder layers with GNN functionality: LlamaDecoderLayerWithGNN : Key class, integrates GNNs into Llama decoder layers, offering methods for constructing adjacency …

Jan 14, 2024 · Figure 4 depicts the model architecture of Llama-2. The model contains an embedding layer followed by D number of decoder blocks and in the end, it has LM_Head …

Llama 2 model consists of a stack of decoder layers. Each decoder layer (or transformer block) is constructed from one self-attention layer and one feed-forward multi-layer perceptron.

Aug 29, 2024 · In this deep dive, we’ll take a unique approach by exploring the model from a reversed perspective. By tracing the workflow backward, we’ll uncover the intricate processes …

Feb 5, 2025 · LLaMA uses a decoder-only transformer architecture similar to GPT models. In this design, the model generates text in an autoregressive manner — predicting one token at a …

Llama Architecture Relevant source files. examples/benchmark.py; lite_llama/models/llama.py; lite_llama/models/qwen2.py; This document details the implementation of the Llama model …

Nov 21, 2024 · LLaMa 3 model consists of one embedding layer, 32 transformer layers and one final dense layer. The following diagram illustrates the high level flow of data from word …

Llama is a family of large language models ranging from 7B to 65B parameters. These models are focused on efficient inference (important for serving language models) by training a smaller …

This class represents a single decoder layer of the LLAMA model. It initializes the layer with the given configuration and layer index. The layer consists of an input layer normalization ( …

Decoder with language modeling is the previous stacked decoder layer plus a linear layer as language prediction head. The langauge prediciton head linearly transforms the hidden state …