README.md

metadata

license: mit

MalayaLLM: Gemma-2 [മലയാളം/Malayalam]

Introducing the Developer:

Discover the mind behind this model and stay updated on their contributions to the field https://www.linkedin.com/in/vishnu-prasad-j/

Model description

The MalayaLLM models have been improved and customized expanding upon the groundwork laid by the original Gemma-2 model.

• Model type: A 9B Gemma-2 finetuned model on Malayalam tokens.
• Language(s): Malayalam and English
• Datasets: CohereForAI/aya_dataset
• Source Model: MalayaLLM_Gemma_2_9B_Base_V1.0
• Instruct Model: MalayaLLM_Gemma_2_9B_Instruct_V1.0
• Training Precision: float16
• Github Repo: MalayaLLM-Gemma2-9B

Old Model

Gemma trained model is here :MalayaLLM: Gemma-7B

How to run GGUF

• llama.cpp Web Server

  • The web server is a lightweight HTTP server that can be used to serve local models and easily connect them to existing clients.

• Building llama.cpp

  • To build llama.cpp locally, follow the instructions provided in the build documentation.

• Running llama.cpp as a Web Server

  • Once you have built llama.cpp, you can run it as a web server. Below is an example of how to start the server:

    llama-server.exe -m gemma_2_9b_instruction.Q4_K_M.gguf -ngl 42 -c 128 -n 100
    

• Accessing the Web UI

  • After starting the server, you can access the basic web UI via your browser at the following address: http://localhost:8080

Made Using UNSLOTH

Thanks to Unsloth, the process of fine-tuning large language models (LLMs) has become much easier and more efficient.

🌟Happy coding💻🌟