moe_lora_transformer_hash_mha_r8_alpha32

This is a Mixture of Experts (MoE) transformer model with LoRA (Low-Rank Adaptation) experts trained for text summarization.

Model Details

• Model Type: Mixture of Experts Transformer with LoRA
• Router Type: Hash Router
• Attention Type: Multi-Head Attention (MHA)
• LoRA Configuration:
  • Rank (r): 8
  • Alpha: 32
• Training Epochs: 3
• Task: Text Summarization

Architecture

This model uses:

• LoRA-based expert networks for parameter efficiency
• Hash routing for expert selection
• Multi-head attention mechanism
• Trained on text summarization tasks

Usage

from transformers import AutoTokenizer, AutoModel

tokenizer = AutoTokenizer.from_pretrained("ManasMittal2005/moe_lora_transformer_hash_mha_r8_alpha32")
model = AutoModel.from_pretrained("ManasMittal2005/moe_lora_transformer_hash_mha_r8_alpha32")

Training

The model was trained using the ANLP-3 assignment framework with:

• LoRA experts for parameter efficiency
• Hash router for deterministic expert selection
• Standard multi-head attention
• Optimized for text summarization tasks