ZEUS-8B-V8 Model Summary

Introduction

ZEUS-8B-V8 is a language model developed using mergekit, which combines several pre-trained models to enhance text generation capabilities. It utilizes advanced merging techniques to create a robust model suited for various text generation tasks.

Architecture

The ZEUS-8B-V8 model was created using the DARE TIES merge method. It integrates elements from several models, including:

• SicariusSicariiStuff/LLAMA-3_8B_Unaligned_BETA
• arcee-ai/Llama-3.1-SuperNova-Lite
• akjindal53244/Llama-3.1-Storm-8B

These models were merged into a base model, unsloth/Meta-Llama-3.1-8B-Instruct, with specific configurations such as bfloat16 data type and weighted layer contributions.

Training

The model's training involved merging several pre-trained models using specified layer ranges and parameters to optimize performance across different tasks. The merging process considers layer density and weight, ensuring each model's contribution is balanced according to the configuration.

Guide: Running Locally

1. Installation: Ensure you have the transformers library installed.

   pip install transformers
   

2. Access the Model:

   • Clone the model repository or download the necessary files from Hugging Face.

3. Load the Model:

   from transformers import AutoModelForCausalLM, AutoTokenizer
   
   tokenizer = AutoTokenizer.from_pretrained("T145/ZEUS-8B-V8")
   model = AutoModelForCausalLM.from_pretrained("T145/ZEUS-8B-V8")
   

4. Inference:

   inputs = tokenizer("Your text here", return_tensors="pt")
   outputs = model.generate(**inputs)
   print(tokenizer.decode(outputs[0]))
   

5. Cloud GPUs: For efficient processing, consider using cloud GPU services like AWS, Google Cloud, or Azure to handle the model's computational requirements.

License

The ZEUS-8B-V8 model is released under the llama3.1 license. Please refer to the specific licensing terms for usage and distribution guidelines.