f 5 8b

Introduction

The F-5-8B model is a merged pre-trained language model utilizing the SLERP merge method, created by combining two models: F-4-8B and F-2-8B. It uses the transformers library and incorporates advanced merging techniques to enhance performance.

Architecture

This model is based on a combination of two models using the SLERP method, which smoothly interpolates between parameter spaces. The merging process involved specific layer configurations and parameter adjustments to optimize performance.

Training

The model does not involve traditional training but instead combines pre-trained models using the SLERP merge method. This method involves interpolating between the layers of two models across specified ranges and applying constraints on parameters such as self-attention and multi-layer perceptrons (MLP) with a set value of 0.1.

Guide: Running Locally

1. Setup Environment: Install the necessary libraries using pip:

   pip install transformers safetensors
   

2. Download Model: Use the Hugging Face Hub to download the F-5-8B model.

3. Load Model: Load the model in your Python script:

   from transformers import AutoModelForCausalLM, AutoTokenizer
   
   model = AutoModelForCausalLM.from_pretrained('jaspionjader/f-5-8b')
   tokenizer = AutoTokenizer.from_pretrained('jaspionjader/f-5-8b')
   

4. Inference: Utilize the model for text generation tasks.

Cloud GPUs: For efficiency, consider using cloud services like AWS, GCP, or Azure, which provide access to powerful GPUs.

License

Refer to the Hugging Face repository or model card for specific licensing details regarding the F-5-8B model.