ValueError: Invalid cache_implementation (offloaded).

[leigao97]

System Info

• transformers version: 4.46.2
• Platform: Linux-5.15.0-1049-oracle-x86_64-with-glibc2.35
• Python version: 3.10.14
• Huggingface_hub version: 0.25.1
• Safetensors version: 0.4.5
• Accelerate version: 1.0.1
• Accelerate config: not found
• PyTorch version (GPU?): 2.4.1+cu121 (True)
• Tensorflow version (GPU?): not installed (NA)
• Flax version (CPU?/GPU?/TPU?): not installed (NA)
• Jax version: not installed
• JaxLib version: not installed
• Using distributed or parallel set-up in script?:
• Using GPU in script?:
• GPU type: NVIDIA A100-SXM4-40GB

Who can help?

No response

Information

• The official example scripts
• My own modified scripts

Tasks

• An officially supported task in the examples folder (such as GLUE/SQuAD, ...)
• My own task or dataset (give details below)

Reproduction

I am following the official example to enable KV cache offloading. https://huggingface.co/docs/transformers/en/kv_cache#offloaded-cache

And I got the error message:

  File "/transformers/generation/configuration_utils.py", line 726, in validate
    raise ValueError(
ValueError: Invalid `cache_implementation` (offloaded). Choose one of: ['static', 'offloaded_static', 'sliding_window', 'hybrid', 'mamba', 'quantized', 'static']

Expected behavior

I expected that cache_implementation="offloaded" is a valid option taken by model.generate(). After enabling KV cache offloading, the peak memory usage should go down and inference time should go up.