Resolve Triton.ops Missing Imports on Kaggle Runtimes

[purvanshjoshi]

Technical Overview

Starting with version 0.45.1, bitsandbytes introduces dependencies on the triton compiler backend for accelerated kernel operations. On certain environments (such as standard Kaggle instances), importing the library throws ModuleNotFoundError: No module named 'triton.ops' because the triton library is either missing or has outdated path bindings.

Affected Modules

• Library: bitsandbytes and triton

Detailed Traceback / Context

ModuleNotFoundError: No module named 'triton.ops'

Acceptance Criteria

1. Version Parity: Pre-training setup logic automatically installs and binds compatible triton and bitsandbytes versions.
2. Quantized Stability: The quantization module functions correctly without raising missing Triton import warnings.

Proposed Implementation Approach

Document and script an optimized dependency installation routine:

# Pin exact compatible pairings for CUDA 12.8
pip install triton==3.2.0 --no-deps
pip install bitsandbytes==0.45.1

Alternatively, document a fallback to bitsandbytes==0.43.3 (which does not depend on Triton) for environments where compiling Triton from source is restricted.

Severity & Priority

• Severity: High (Blocks model loading with quantization)
• Priority: P1

[Saksham-dev-del]

Hi @purvanshjoshi,

I would like to work on this issue. I will update the environment setup script to pin compatible triton and bitsandbytes versions (triton==3.2.0 with bitsandbytes==0.45.1) for CUDA 12.8 runtimes, and document a fallback to bitsandbytes==0.43.3 for environments where compiling Triton is restricted.

I will verify the fix on a Kaggle runtime to confirm the ModuleNotFoundError: No module named 'triton.ops' no longer occurs and that quantized model loading remains stable.

Could you please assign this issue to me? I will submit a PR for review once complete.