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puchuneko/GLM-4-32B-0414-Z1-SLERP
GLM-4-32B-0414-Z1-SLERP is a text generation model from puchuneko. Use it when you need the model to write or continue text. It is set up for transformers. The card lists the license as mit.
A SLERP merge of GLM-4-32B-0414 (instruct) and GLM-Z1-32B-0414 (reasoning) at t=0.3 (~70% instruct / 30% reasoning). No Korean fine-tuning — this is an experimental base artifact, shared transparently.
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From the Hugging Face model README
A SLERP merge of GLM-4-32B-0414 (instruct) and GLM-Z1-32B-0414 (reasoning) at t=0.3 (~70% instruct / 30% reasoning). No Korean fine-tuning — this is an experimental base artifact, shared transparently.
On GSM8K (5-shot, 300 samples) this merge scores 94.0% vs 88.3% for its instruct parent — a +5.7pp gain (~2.4 sigma, statistically significant). It absorbs some of the reasoning parent's math skill while keeping the instruct parent's concise answering. This is the only benchmark run. Not a SOTA claim.
| Model | GSM8K (5-shot) | n | stderr |
|---|---|---|---|
| This merge (SLERP t=0.3) | 0.940 | 300 | +/-0.014 |
| GLM-4-32B-0414 (instruct parent) | 0.883 | 300 | +/-0.019 |
| GLM-Z1-32B-0414 (reasoning parent) | 0.43* | 100 | +/-0.05 |
*The reasoning parent's low score is an evaluation artifact: its long chain-of-thought is truncated at the default generation length — not its true ability.
merge_method: slerp
base_model: zai-org/GLM-4-32B-0414
models:
- model: zai-org/GLM-Z1-32B-0414
parameters:
t: 0.3
dtype: bfloat16
Made with mergekit. Note: task-vector methods (dare_ties / ties with a base) collapsed this instruct+reasoning pair into incoherent multilingual/code output; only SLERP (direct interpolation, no base subtraction) yielded a coherent model.
GLM-4-32B-0414 / GLM-Z1-32B-0414 (c) Zhipu AI (Z.ai), MIT License. Merged with mergekit (Arcee AI).