M F A N N Llama3.1 Abliterated S L E R P V5

Introduction

MFANN-Llama3.1-Abliterated-SLERP-V5 is a pre-trained language model developed by merging two other models using the SLERP method. It is designed for applications in text generation within the Hugging Face ecosystem.

Architecture

The model is a combination of two existing models: mlabonne/Meta-Llama-3.1-8B-Instruct-abliterated and netcat420/MFANNv0.25. The merging process utilized the SLERP method to integrate layers from both models. Specifically, layers 0 to 32 from each model were considered in the merging process.

Training

The training configuration involves a YAML setup that specifies the models and layers for merging. The parameters include specific filters and values for self_attn and mlp, with a general parameter value set at 0.5. The data type used for processing is bfloat16.

Guide: Running Locally

1. Clone the Repository: Download the model using Git or Hugging Face's transformers library.
2. Install Dependencies: Ensure the transformers library and any other necessary packages are installed.
3. Load the Model: Use the from_pretrained method in the transformers library to load the model.
4. Run Inference: Input text data and execute the model to generate responses.

For optimal performance, consider using cloud-based GPUs such as those offered by AWS, Google Cloud, or Azure for faster processing.

License

The model is provided under the terms specified by the original model creators. Ensure compliance with all applicable licenses when using or distributing the model.