Welcome to your comprehensive guide on getting started with CodeLlama 34B Instruct! This cutting-edge model by Meta offers exciting capabilities in code synthesis and understanding. Here’s how to effectively download, run, and troubleshoot this robust tool.

Understanding CodeLlama 34B Instruct

CodeLlama 34B is like a Swiss Army knife for programmers. Just as a Swiss Army knife can assist in various tasks — from opening bottles to fixing screws — CodeLlama helps solve coding problems, generate code snippets, and even assist in debugging. With its 34 billion parameters, the model is designed to tackle diverse coding challenges with ease.

How to Download GGUF Files

To get started with CodeLlama 34B Instruct, follow these simple steps to download the GGUF files:

• Using Text-Generation-WebUI:

  Go to the “Download Model” section and enter the repository name: TheBloke/CodeLlama-34B-Instruct-GGUF. Next, specify a filename — for example, codellama-34b-instruct.q4_K_M.gguf. Click “Download” to fetch the model.

• Using Command Line:

  If you prefer command line, install the huggingface-hub library:

  pip3 install huggingface-hub=0.17.1

  Then, download the model file with:

  huggingface-cli download TheBloke/CodeLlama-34B-Instruct-GGUF codellama-34b-instruct.q4_K_M.gguf --local-dir . --local-dir-use-symlinks False

How to Run CodeLlama 34B Instruct

Once you have the model downloaded, it’s time to run it. Here’s a straightforward way to execute it:

• Using llama.cpp:

  Make sure you’re using a compatible version of llama.cpp. Use the following command to run:

  ./main -ngl 32 -m codellama-34b-instruct.q4_K_M.gguf --color -c 4096 --temp 0.7 --repeat_penalty 1.1 -n -1 -p [INST] Write code to solve the following coding problem that obeys the constraints and passes the example test cases. Please wrap your code answer using :prompt[INST]

• Using Python:

  If you prefer to work in Python, utilize the ctransformers library:

  from ctransformers import AutoModelForCausalLM
  llm = AutoModelForCausalLM.from_pretrained('TheBloke/CodeLlama-34B-Instruct-GGUF', model_file='codellama-34b-instruct.q4_K_M.gguf', model_type='llama', gpu_layers=50)
  print(llm('AI is going to'))

Troubleshooting

Here are some common issues you might encounter while using CodeLlama 34B Instruct and how to resolve them:

• Model not downloading: Ensure you’re connected to the internet and using the correct repository URL.
• Compatibility issues: Check if your version of llama.cpp is updated and matches the commit mentioned in the documentation.
• CUDA errors: Confirm that your GPU is correctly configured and supports the required CUDA version.

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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.