Fix: Cache model in huggingface_local to prevent OOM (Issue #449)

[adambarla]

Problem

When fn_completions is set to huggingface_local_completions, alpaca_eval reloads the model for every chunk of data. This leads to:

1. Significant time overhead (reloading large models repeatedly).
2. OOM errors because the previous model isn't always garbage collected immediately before the new one loads.

Fixes #449.

Solution

Implemented module-level caching for the model and tokenizer, following the existing pattern in vllm_local.py.

• Added _get_or_load_model helper function.
• Uses global _loaded_model to persist the model across calls.
• Checks if the requested model matches the cached one.
• Explicitly unloads/GCs the old model if switching to a new one.

Testing

Tested locally with a dataset split into multiple chunks. Verified that:

• Model loads only once.
• GPU memory usage remains stable across chunks.
• "Reusing cached model" logs appear for subsequent chunks.