Magnolia v3 Gemma2 8k 9 B

Introduction

MAGNOLIA-V3-GEMMA2-8K-9B is a pre-trained language model designed for text generation, created using the mergekit tool. It combines capabilities from different models to enhance performance using a specific merging technique.

Architecture

The model employs a merging technique called SLERP (Spherical Linear Interpolation) to integrate features from multiple pre-trained models. It is built using the transformers library and is structured to optimize text generation tasks. The model is a merger of grimjim/Gigantes-v1-gemma2-9b-it and grimjim/Magnolia-v2-Gemma2-8k-9B.

Training

MAGNOLIA-V3-GEMMA2-8K-9B was trained using a YAML configuration that specifies the models involved, the merging method, and the parameters like dtype: bfloat16. The SLERP method is utilized to blend the models seamlessly, focusing on maintaining the strengths of each.

Guide: Running Locally

1. Install Dependencies
   Ensure you have Python and the transformers library installed. Use pip to install any additional packages required.

   pip install transformers
   

2. Download the Model
   Access the model via the Hugging Face Model Hub and download it for local use.

3. Load the Model
   Use the transformers library to load the model in your Python environment.

   from transformers import AutoModelForCausalLM, AutoTokenizer
   
   tokenizer = AutoTokenizer.from_pretrained("grimjim/Magnolia-v3-Gemma2-8k-9B")
   model = AutoModelForCausalLM.from_pretrained("grimjim/Magnolia-v3-Gemma2-8k-9B")
   

4. Inference
   For text generation, input your text prompt and generate responses using the model.

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

5. Cloud GPU Recommendation
   For optimal performance, it is recommended to run the model on a cloud GPU service such as AWS, Google Cloud, or Azure.

License

The MAGNOLIA-V3-GEMMA2-8K-9B is released under the gemma license. Please refer to the license terms for usage guidelines and restrictions.