MalayaLLM: Gemma [മലയാളം/Malayalam]

Introducing the Developer:

Model description

• Model type: A 7B Gemma finetuned model on Malayalam tokens.
• Language(s): Malayalam and English
• Datasets: CohereForAI/aya_dataset
• Source Model: MalayaLLM_Gemma_7B_Base_V1
• Instruct Model: MalayaLLM_Gemma_7B_Instruct_V1
• Training Precision: float16
• Github Repo: MalayaLLM-Gemma

Model Update

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_7b_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💻🌟