Welcome to your step-by-step guide on how to utilize the GGUF formatted model, based on the Alibaba NLP GTE Qwen 2 framework. This guide will walk you through the necessary installation and execution commands, making it easy for you to get started.

Getting Started

To begin, you’ll need to convert the original model into the GGUF format and set up the necessary environment to use it. Here’s how you can do this:

1. Install llama.cpp

First, you need to install the llama.cpp package. This can be done easily via brew, which works seamlessly on both Mac and Linux environments:

brew install llama.cpp

2. Choose Your Method

You can choose to run the GGUF model either through the Command Line Interface (CLI) or the server. Below are the commands to do so:

Using CLI:

llama-cli --hf-repo VenkatNDivi77gte-Qwen2-7B-instruct-Q4_K_M-GGUF --hf-file gte-qwen2-7b-instruct-q4_k_m.gguf -p "The meaning to life and the universe is"

Using Server:

llama-server --hf-repo VenkatNDivi77gte-Qwen2-7B-instruct-Q4_K_M-GGUF --hf-file gte-qwen2-7b-instruct-q4_k_m.gguf -c 2048

3. Clone and Build llama.cpp

If you want more control or to run specific configurations, you might prefer to clone the repository and build it from source.

Step 1: Clone the Repository

git clone https://github.com/ggerganov/llama.cpp

Step 2: Build with Specific Flags

Move into the `llama.cpp` directory:

cd llama.cpp

And build it using the following command with necessary flags:

LLAMA_CURL=1 make

Step 3: Run Inference

Now run inference using either of the following commands:

llama-cli --hf-repo VenkatNDivi77gte-Qwen2-7B-instruct-Q4_K_M-GGUF --hf-file gte-qwen2-7b-instruct-q4_k_m.gguf -p "The meaning to life and the universe is"

or

llama-server --hf-repo VenkatNDivi77gte-Qwen2-7B-instruct-Q4_K_M-GGUF --hf-file gte-qwen2-7b-instruct-q4_k_m.gguf -c 2048

Troubleshooting

Should you encounter any issues while using the model, here are some troubleshooting ideas:

• Make sure you have installed all dependencies, particularly when using building flags for GPU support.
• If you face issues with memory, try adjusting the context parameter (-c) when using the server.
• Keep an eye on the terminal output for any error messages that might direct you towards the problem.

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Conclusion

Congratulations! You have successfully set up the GGUF formatted model from Alibaba’s NLP GTE Qwen 2. Explore its capabilities and experiment with various inputs to harness its full potential. At fxis.ai, we believe that such advancements are crucial for the future of AI, as they enable more comprehensive and effective solutions. Our team is continually exploring new methodologies to push the envelope in artificial intelligence, ensuring that our clients benefit from the latest technological innovations.