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malaiwah/fruit-phase1-ckpt
fruit-phase1-ckpt is a machine learning model from malaiwah. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for pytorch. The card lists the license as apache-2.0.
Model-only weights, resumable optimizer/RNG checkpoints, metrics, and plots for GLM-5.2-SIQ-Fruit. This is a 151.54 GB (141.14 GiB) training archive, not a Transformers or vLLM serving repository.
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Updated Aug 7, 2026
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.pt152 GB · 100%
From the Hugging Face model README
Model-only weights, resumable optimizer/RNG checkpoints, metrics, and plots for GLM-5.2-SIQ-Fruit. This is a 151.54 GB (141.14 GiB) training archive, not a Transformers or vLLM serving repository.

Phase 1 completed 57,293 steps and about 5.43B sampled tokens across MAIN,
LONG, DISTILL, QNOISE, and SFT. The plot is generated from the durable metrics
ledger; raw validation points are in progress/fruit_v1_val.jsonl.
| file | stage | size |
|---|---|---|
final/fruit_v1_main.pt | MAIN, 4,096 context | 10.081 GB |
final/fruit_v1_long.pt | LONG, 16,384 context | 10.081 GB |
final/fruit_v1_final.pt | DSA indexer DISTILL; pre-anneal control | 10.081 GB |
final/fruit_v1_annealed.pt | QNOISE anneal; published base-model source | 10.081 GB |
final/fruit_v1_instruct.pt | assistant-masked SFT | 10.081 GB |
The canonical base release source is final/fruit_v1_annealed.pt, SHA-256
98ac7cb4f7799194424782b505d622069fecf4dbca5f5acb2658f2a66c3631f6.
The Instruct source is final/fruit_v1_instruct.pt, SHA-256
32dbf82d40b88a92b8dccd563c593b5971be358cf11895eb150f18644ff93c27.
checkpoints/*_ckpt.pt and final/fruit_v1_instruct_ckpt.pt are roughly
20.2 GB each. They contain model parameters, optimizer state, step and token
counters, and Python/NumPy/Torch/CUDA RNG state. Use them only with the
matching trainer and geometry in
proxy-fruit.
These full-state files are Python pickle containers and require trusted
torch.load(..., weights_only=False). Do not load a checkpoint from an
untrusted revision. MANIFEST.sha256 authenticates the published archive
files except the card, Git attributes, and the manifest itself.
The Phase-1 weights predate the fail-closed Run-2 markers
serve_conv_v and rope_theta_trained. They use:
eh_proj(cat[hidden, embed]) input order;mlp.w_gate, mlp.w_up, mlp.w_down).Any export or resume must explicitly select the legacy convention. The maintained exporter applies the RoPE channel permutation and MTP input-half swap. Treating these files as serving-native silently corrupts logits and MTP behavior.
Avoid cloning the complete 151 GB repository when only one stage is needed:
hf download malaiwah/fruit-phase1-ckpt \
final/fruit_v1_annealed.pt \
--local-dir ./fruit-checkpoint
sha256sum ./fruit-checkpoint/final/fruit_v1_annealed.pt
For resume, download the matching *_ckpt.pt plus the tokenizer/data inputs
documented by the trainer. Model-only .pt files cannot resume optimizer or
RNG state.
The files are retained for reproducibility and codec experiments. They are not
packaged for AutoModel.from_pretrained() and should not be presented as a
ready-to-serve model.