M T M Merge gemma 2 9 B

Introduction
The MTM-Merge-Gemma-2-9B model is a text generation language model created by merging pre-trained models using the mergekit tool. This model leverages the SLERP merge method to combine multiple language models, enhancing its capabilities in generating coherent and contextually relevant text.

Architecture
The model architecture involves merging two pre-existing models: zelk12/MTM-Merge-MMMUBI-gemma-2-9B and zelk12/MTM-Merge-GMA-gemma-2-9B. The merger utilizes the SLERP (Spherical Linear Interpolation) method, which aims to maintain a balance between the features of the models being merged. The base model for this architecture is zelk12/MTM-Merge-GMA-gemma-2-9B, and the model operates using the bfloat16 data type.

Training
Training involves combining the features of the two specified models using the SLERP method with a parameter t set to 0.25. This parameter controls the interpolation between the models, affecting how much influence each model has in the final merged model.

Guide: Running Locally

1. Install Dependencies: Ensure you have Python and the Hugging Face Transformers library installed.

   pip install transformers
   

2. Download the Model: Retrieve the MTM-Merge-Gemma-2-9B model files from the Hugging Face model hub.
3. Load the Model: Use the Transformers library to load the model into your Python environment.

   from transformers import AutoModelForCausalLM, AutoTokenizer
   
   tokenizer = AutoTokenizer.from_pretrained("zelk12/MTM-Merge-gemma-2-9B")
   model = AutoModelForCausalLM.from_pretrained("zelk12/MTM-Merge-gemma-2-9B")
   

4. Generate Text: Utilize the model to generate text by providing an input prompt.

   input_text = "Once upon a time"
   input_ids = tokenizer.encode(input_text, return_tensors='pt')
   generated_text = model.generate(input_ids)
   print(tokenizer.decode(generated_text[0], skip_special_tokens=True))
   

5. Cloud GPU Recommendation: For optimal performance, especially with large models like MTM-Merge-Gemma-2-9B, consider using cloud GPUs through services like AWS, Google Cloud, or Azure.

License
The MTM-Merge-Gemma-2-9B model is distributed under the Gemma license. Ensure you review and comply with this license when using the model.