Add CI integration for Spark-X2.5 models

[dongjiang1989]

Summary

This PR adds CI integration for Spark-X2.5 models (1.7B and 4B variants) to the ExecuTorch test infrastructure.

Changes:

• Added spark_x2_5_1_7b and spark_x2_5_4b model support to .ci/scripts/test_torchao_huggingface_checkpoints.sh
• Added both models to the CI test matrix in .github/workflows/trunk.yml
• Configured XNNPACK (x86_64) and TorchAO (ARM64) backend testing for both variants

The Spark-X2.5 model infrastructure (configs, weight conversion, documentation) already exists in the codebase. This PR completes the integration by adding automated CI testing.

Model specifications:

• Spark-X2.5-1.7B: 28 layers, hybrid attention architecture (3 sliding + 1 full attention)
• Spark-X2.5-4B: 36 layers, hybrid attention architecture
• Both support 8da4w quantization and extended context (up to 1M tokens)

Hugging Face models:

• XHToken/Spark-X2.5-1.7B
• XHToken/Spark-X2.5-4B

Test plan

The changes add CI test coverage for both Spark-X2.5 model variants:

1. Automated CI tests (via GitHub Actions):

   • Both models will be tested on x86_64 with XNNPACK backend
   • Both models will be tested on ARM64 with TorchAO backend
   • Tests verify model export, weight conversion, and basic inference

2. Manual testing (to verify locally):

   # Test Spark-X2.5-1.7B
   bash .ci/scripts/test_torchao_huggingface_checkpoints.sh spark_x2_5_1_7b --test_with_runner
   
   # Test Spark-X2.5-4B
   bash .ci/scripts/test_torchao_huggingface_checkpoints.sh spark_x2_5_4b --test_with_runner

3. Unit tests (already present):

   pytest examples/models/spark_x2_5/test_spark_x2_5.py -v

The CI script validates:

• Model download from Hugging Face
• Weight conversion to Meta format
• Model export with 8da4w quantization
• File size bounds (2GB for 1.7B, 5GB for 4B)
• Inference via llama_main runner

cc @larryliu0820 @mergennachin @cccclai @helunwencser @jackzhxng @digantdesai @nil-is-all

[pytorch-bot]

🔗 Helpful Links

🧪 See artifacts and rendered test results at hud.pytorch.org/pr/pytorch/executorch/23525

• 📄 Preview Python docs built from this PR

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⚠️ 24 Awaiting Approval

As of commit 04bf8e9 with merge base f2575be ():

AWAITING APPROVAL - The following workflows need approval before CI can run:

• Build Aarch64 Linux CUDA Wheels (gh)
• Build Aarch64 Linux Wheels (gh)
• Build documentation (gh)
• Build Linux CUDA Wheels (gh)
• Build Linux Wheels (gh)
• Build macOS Wheels (gh)
• Build Presets (gh)
• Build Windows CUDA Wheels (gh)
• Build Windows Wheels (gh)
• Cadence Build & Test (gh)
• Lint (gh)
• periodic (gh)
• pull (gh)
• Test ARM Backend (gh)
• Test CoreML Backend (gh)
• Test Cortex-M Backend (gh)
• Test NXP Backend (gh)
• Test QNN Backend (gh)
• Test QNN Windows MSVC build (gh)
• Test Vulkan Backend (gh)
• Test WebGPU Backend (gh)
• Test XNNPACK Backend (gh)
• trunk (gh)
• Windows MSVC Build (gh)

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[github-actions]

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[nil-is-all]

@dongjiang1989 could you fix the CI failures? Do ping when ready for review.

[nil-is-all]

@dongjiang1989 this revert would have resolved the failing CI. Could you try with this and ping to trigger CI workflows?

[dongjiang1989]

@dongjiang1989 could you fix the CI failures? Do ping when ready for review.

Thx @nil-is-all rebase done.
Please recheck it, thanks

[dongjiang1989]

Hey @nil-is-all

CI is failing because /mnt/hf_cache on the runners is read-only. The existing models (qwen3, phi_4_mini, lfm2_5) are pre-cached there, but XHToken/Spark-X2.5-1.7B and XHToken/Spark-X2.5-4B are not, so hf download fails with:

OSError: [Errno 30] Read-only file system: /mnt/hf_cache/hub/models--XHToken--Spark-X2.5-*

Please add pre-cache the two Spark-X2.5 models in /mnt/hf_cache?

[nil-is-all]

Hey @nil-is-all

CI is failing because /mnt/hf_cache on the runners is read-only. The existing models (qwen3, phi_4_mini, lfm2_5) are pre-cached there, but XHToken/Spark-X2.5-1.7B and XHToken/Spark-X2.5-4B are not, so hf download fails with:

OSError: [Errno 30] Read-only file system: /mnt/hf_cache/hub/models--XHToken--Spark-X2.5-*

Please add pre-cache the two Spark-X2.5 models in /mnt/hf_cache?

@dongjiang1989 I'd suggest making the script not depend on the shared cache being pre-populated.
The script only needs /mnt/hf_cache to be readable. The failure is hf download trying to create models--XHToken--Spark-X2.5-* in a read-only mount. If you point it at a writable workspace dir for these models, the download lands somewhere writable, But I'll run CI to check if it still flags it.

[dongjiang1989]

@dongjiang1989 I'd suggest making the script not depend on the shared cache being pre-populated.

Thanks @nil-is-all Change model download dir to custom dir.
Please recheck it, 🤭