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 multi head 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
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