⁉️ Frequently Asked Questions

How much VRAM a LLM model consumes?

By default, Tabby operates in int8 mode with CUDA, requiring approximately 8GB of VRAM for CodeLlama-7B.

For ROCm the actual limits are currently largely untested, but the same CodeLlama-7B seems to use 8GB of VRAM as well on a AMD Radeon™ RX 7900 XTX according to the ROCm monitoring tools.

What GPUs are required for reduced-precision inference (e.g int8)?

• int8: Compute Capability >= 7.0 or Compute Capability 6.1
• float16: Compute Capability >= 7.0
• bfloat16: Compute Capability >= 8.0

To determine the mapping between the GPU card type and its compute capability, please visit this page

How to utilize multiple NVIDIA GPUs?

Tabby only supports the use of a single GPU. To utilize multiple GPUs, you can initiate multiple Tabby instances and set CUDA_VISIBLE_DEVICES (for cuda) or HIP_VISIBLE_DEVICES (for rocm) accordingly.

My AMD device isn't supported by ROCm

You can use the HSA_OVERRIDE_GFX_VERSION variable if there is a similar GPU that is supported by ROCm you can set it to that.

For example for RDNA2 you can set it to 10.3.0 and to 11.0.0 for RDNA3.

How can I use my own model with Tabby?

Please follow the Tabby Model Specification to create a directory with the specified files. You can then pass the directory path to --model or --chat-model to start Tabby.

Can I use local model with Tabby?

Tabby also supports loading models from a local directory that follow our specifications as outlined in MODEL_SPEC.md.