Welcome to our comprehensive guide on accessing CodeGemma through Hugging Face! If you’re keen on experimenting with AI using advanced models like CodeGemma, follow these steps to get started effortlessly.

Step 1: Google’s Usage License

To start using CodeGemma, you need to agree to Google’s usage license. As a prerequisite, ensure you are logged into your Hugging Face account. Once you’re logged in, simply follow the prompt on Hugging Face to acknowledge the license.

• Log in to your Hugging Face account.
• Click on the provided button to acknowledge the license.

Step 2: Downloading CodeGemma

After agreeing to the license, you can easily download the desired version of CodeGemma. Here’s a list of available downloads:

Filename                     Quant type   File Size   Description
---------------------------------------------------------------
[codegemma-7b-Q8_0.gguf]       Q8_0         9.07GB      Extremely high quality, generally unneeded but max available quant.  
[codegemma-7b-Q6_K.gguf]       Q6_K         7.01GB      Very high quality, near perfect, recommended.  
[codegemma-7b-Q5_K_M.gguf]     Q5_K_M       6.14GB      High quality, recommended.  
[codegemma-7b-Q5_K_S.gguf]     Q5_K_S       5.98GB      High quality, recommended.  
[codegemma-7b-Q4_K_M.gguf]     Q4_K_M       5.32GB      Good quality, uses about 4.83 bits per weight, recommended.  
[codegemma-7b-Q4_K_S.gguf]     Q4_K_S       5.04GB      Slightly lower quality with more space savings, recommended.  
[codegemma-7b-IQ4_NL.gguf]     IQ4_NL       5.01GB      Decent quality, slightly smaller than Q4_K_S with similar performance recommended.  
[codegemma-7b-IQ4_XS.gguf]     IQ4_XS       4.76GB      Decent quality, smaller than Q4_K_S with similar performance, recommended.
...

Choose the quantization level that best fits your needs based on your system’s RAM and VRAM availability.

Step 3: Choosing the Right File

Determining the right file for your setup is crucial for optimal performance. Here are some tips to guide your decision:

• Determine the total RAM and VRAM available on your system.
• If you want fast performance, select a quant that is 1-2GB smaller than your GPU’s VRAM.
• For the best possible quality, sum your system RAM and GPU VRAM, then choose a quant accordingly.
• If you prefer simplicity, opt for the K-quants (e.g., Q5_K_M).
• For more detailed performance, consider the I-quants (e.g., IQ4_XS), which provide better performance at the cost of speed for specific applications.

Troubleshooting Tips

If you encounter any issues while trying to download or utilize CodeGemma, consider the following troubleshooting techniques:

• Verify that you are logged into your Hugging Face account and have acknowledged the usage license.
• Check your system’s RAM and VRAM to ensure compatibility with the selected model size.
• If the model fails to load, try switching between K-quants and I-quants based on your system’s specifications.

For additional assistance and updates, stay connected with fxis.ai.

Conclusion

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.

Following these steps should enable you to access and utilize CodeGemma seamlessly. Happy coding!