--- license: apache-2.0 --- # MatMul-Free LL ## Model Details [[Paper](https://arxiv.org/abs/2406.02528)] [[Code](https://github.com/ridgerchu/matmulfreellm/tree/master)] MatMul-Free LM is a language model architecture that eliminates the need for Matrix Multiplication (MatMul) operations. This repository provides an implementation of MatMul-Free LM that is compatible with the 🤗 Transformers library. ![MatMul-Free LM](https://raw.githubusercontent.com/ridgerchu/matmulfreellm/master/__assets__/main.png) ## Scaling Law We evaluate how the scaling law fits to the 370M, 1.3B and 2.7B parameter models in both Transformer++ and our model. For a fair comparison, each operation is treated identically, though our model uses more efficient ternary weights in some layers. Interestingly, the scaling projection for our model exhibits a steeper descent compared to Transformer++, suggesting our architecture is more efficient in leveraging additional compute to improve performance. ![Scaling Law](https://raw.githubusercontent.com/ridgerchu/matmulfreellm/master/__assets__/scaling_law.png) ## Usage We provide the implementations of models that are compatible with 🤗 Transformers library. Here's an example of how to initialize a model from the default configs in ```matmulfreelm```: This is a huggingface-compatible library that you can use such command to initialize the model with huggingface ```AutoModel```: ```shell pip install transformers pip install -U git+https://github.com/ridgerchu/matmulfreellm ``` ```python from mmfreelm.models import HGRNBitConfig from mmfreelm.layers import hgrn_bit from transformers import AutoModelForCausalLM model = AutoModelForCausalLM.from_pretrained("ridger/MMfreeLM-2.7B") ``` ## Pre-trained Model Zoo | Model Size | Layer | Hidden dimension | Trained tokens | | [370M](https://huggingface.co/ridger/MMfreeLM-370M) | 24 | 1024 | 15B | | :---: | :---: | :---: | :---: | | [1.3B](https://huggingface.co/ridger/MMfreeLM-1.3B) | 24 | 2048 | 100B | | [2.7B](https://huggingface.co/ridger/MMfreeLM-2.7B) | 32 | 2560 | 100B |