Xnhyacinth/LongWorld-Research-Checkpoints

LongWorld Research Checkpoints

Three complete, final step-680 SFT weight exports used as LongWorld related-work baselines. Each subfolder contains its own model shards, index, configuration, tokenizer and processor files. The variants retain independent learned weights.

Subfolder	Starting model	SFT data
acc-step680	Qwen3.5-4B Instruct	ACC
base-acc-step680	Qwen3.5-4B-Base	ACC
base-longtrace-step680	Qwen3.5-4B-Base	LongTraceRL

These are the final aligned step-680 exports, not a selection of the best validation checkpoint. The Base LongTrace run was trained independently from the Base ACC run. The training inputs are in the 128k baseline dataset. They are related-work baselines, not checkpoints trained on the LongWorld workflow-probe product.

Download one variant

from huggingface_hub import snapshot_download

root = snapshot_download(
    "Xnhyacinth/LongWorld-Research-Checkpoints",
    allow_patterns=["base-acc-step680/*"],
    local_dir="longworld-checkpoints",
)

Use the selected subfolder with a Qwen3.5-compatible inference stack. Structural validation covers the complete safetensors headers, shard index and loading files; inference has not been executed as part of this publication review. ARTIFACTS.json records the exact published paths, sizes and SHA-256 identities.

Only weight and loading files are included. Training arguments, optimizer/RNG state, logs, local restore maps and historical working snapshots are excluded. The original file hashes are retained for the selected exports. Shared tokenizer files appear in each subfolder so each variant can be downloaded independently; no storage-saving claim is made.

The source exports and the upstream Qwen3.5-4B and Qwen3.5-4B-Base cards declare Apache-2.0. The companion training datasets retain their own terms.