Ostixe360/MoMv4-bf16

Model Card for Model ID

Model Details

Model Description

MoM: Mixture of Mixture

This Model is a first test to combine Jamba architecture with bf16 bits linear layers, mixture of attention head and mixture of depth.

The goal is to developpe and test if this kind of architectures have not too much quality loss for a fast inference.

• Model type: Mixture of attention head mixture of depth and mixture of expert bf16 linear layers
• License: Apache licence 2.0

Model Sources [optional]

• Repository: https://github.com/ostix360/optimized-LLM

How to Get Started with the Model

This model has a generation problem because of a softmax application in the mod process

If you want to test this model please look at this repo at this commit

Training Details

• wandb: training detail

Training Data

We use the first ~0.5B tokens of Locutusque/UltraTextbooks to train this model

Training Procedure

We use adam-8 bits with default betas and epsilon values

Preprocessing [optional]

The data fit the model max length i.e. 512 tokens

Training Hyperparameters

Please look at the wandb metadata to see the hyperparameters or the train.py file in the repo

Technical Specifications

Compute Infrastructure

Hardware

• one 4070 ti GPU

Software

• pytorch, transformers etc