VeriLoop-E2-W4A16 / README.md
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Release unmodified quantization with complete saved evaluation metrics and historical reference
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---
license: apache-2.0
base_model: tsinghua-sigs-robot-lab/VeriLoop-E2
base_model_relation: quantized
library_name: transformers
pipeline_tag: text-generation
tags:
- veriloop
- auto-round
- community-quantization
- experimental
---
# VeriLoop-E2-W4A16
Community quantization of [tsinghua-sigs-robot-lab/VeriLoop-E2](https://huggingface.co/tsinghua-sigs-robot-lab/VeriLoop-E2/tree/9379d199adcc44acdf836558037163878e3a37ae), fixed revision `9379d199adcc44acdf836558037163878e3a37ae`. This is not an official Tsinghua release. Model architecture is `Qwen3_5ForConditionalGeneration`; the upstream names the base Qwen3.8-27B.
## What is included
AutoRound W4A16, symmetric group 128, 256 public Pile calibration samples, 512 tokens, 200 iterations, batch 4. Eligible weights are INT4; small hybrid projections, activations and retained weights are BF16. All source tensors are represented; the 333 vision tensors are preserved exactly.
No abliteration was applied to this version.
## Local paired evaluation
Same frozen 1,514 questions, seed 20260816, thinking enabled with the original template and publisher raw-content protocol, greedy decoding, max output 32,768 tokens. These are our legacy sampled/custom scorers, **not official leaderboard results**. IFEval uses a partial custom rule implementation. See EVALUATION.md and evaluation.json for details and validity flags.
| Task | n | Original w4a16 | Ablated w4a16 | Delta pp |
|---|---:|---:|---:|---:|
| mmlu | 150 | 84.00% | 76.00% | -8.00 |
| cmmlu | 150 | 84.67% | 75.33% | -9.33 |
| mmlu_pro | 150 | 78.67% | 70.67% | -8.00 |
| ceval | 150 | 84.00% | 76.00% | -8.00 |
| arc | 150 | 80.67% | 85.33% | +4.67 |
| truthfulqa | 150 | 58.67% | 71.33% | +12.67 |
| gsm8k | 100 | 95.00% | 88.00% | -7.00 |
| math500 | 100 | 75.00% | 73.00% | -2.00 |
| bbh | 150 | 75.33% | 65.33% | -10.00 |
| humaneval | 164 | 89.63% | 89.63% | +0.00 |
| ifeval | 100 | 76.00% | 69.00% | -7.00 |
Overall original → ablated: **80.05% → 76.42%**, difference -3.63 pp; approximate paired 95% CI [-5.894, -1.371] pp. Empty responses: [9, 8]; length-limited responses: [9, 8]. Both stay in the denominator. Empty-rate validity gate: False.
On 100 separate refusal probes (thinking disabled, 2048-token budget), opening-30-word marker counts were **98/100 → 0/100**. Marker absence is not proof of semantic compliance. Truncation/budget hits: [1, 9]; validity: [True, True]. The first 16 probes overlap candidate selection; see the 84-item held-out subset in evaluation.json when available.
## Loading
```bash
vllm serve /path/to/VeriLoop-E2-W4A16 --tensor-parallel-size 2 --generation-config vllm
```
The measured runtime was vLLM 0.29.0 with a local FA2/FP8-KV plugin on dual RTX 3090. That local setup requires its plugin-specific library environment variables; this repository does not bundle the plugin. The command above is a starting point for a compatible installed runtime, not a tested stock-vLLM support matrix. No remote custom model code is required. Vision weights are retained exactly, but visual inference is not validated in this evaluation.
## Scope and limitations
Use the repository-shipped template and publisher raw-content serving protocol. Do not add a Qwen3 reasoning parser: some completed direct answers omit a closing think tag and that parser classifies them entirely as hidden reasoning. Removing it recovered all 33 initial missing-answer cases; streaming/nonstreaming checks passed. Thinking remains enabled. For evaluation, final content is taken after `</think>` when present; normally stopped direct content is retained, while unclosed length-limited output is not scored as an answer.
In llama.cpp content-only mode, remove an echoed opening `<think>` generation-prefix tag before applying answer extraction. It is protocol framing, not answer text. The GGUF preflight was restarted after verifying this correction and the template override; it is excluded from the reported scores.
The author's private VeriLoop Harness is not included or reproduced. Their SWE/Terminal/DeepSWE scores are **not scores for these weights**. This evaluation does not establish long-context, tool-use, vision, agentic performance, or production suitability. Reduced refusal can affect inappropriate-content handling; applications need their own behavior controls. Full semantic refusal review and comprehensive capability equivalence have not been established.
Apache-2.0 is retained from the fixed upstream source; see LICENSE. Source training belongs to its original authors. Community changes are quantization. See release.json and SHA256SUMS for provenance and integrity.
## Complete measurement records and historical comparison
See [all six result columns, test standards and limitations](HISTORICAL-COMPARISON.md), [all 9,084 per-item metric records](evaluation-items.json), [question IDs and hashes](evaluation-question-indices.json), and [400 refusal-probe metric records](evaluation-refusal-items.json). No full-precision baseline was measured. Historical results are not a strictly identical-runtime comparison.