Stage reproducibility bundle for pre-flight
Browse filesThis view is limited to 50 files because it contains too many changes. See raw diff
- .gitignore +4 -0
- README.md +78 -0
- calibration/gte-qwen2-1.5b/gte-Qwen2-1.5B-instruct-mlx-bf16-oQe-s128-l512.npz +3 -0
- calibration/gte-qwen2-1.5b/gte-Qwen2-1.5B-instruct-mlx-bf16-oQe-s128-l512.npz.json +95 -0
- calibration/qwen3-embedding-0.6b/Qwen3-Embedding-0.6B-MLX-BF16-oQe-s128-l512.npz +3 -0
- calibration/qwen3-embedding-0.6b/Qwen3-Embedding-0.6B-MLX-BF16-oQe-s128-l512.npz.json +95 -0
- calibration/qwen3-embedding-8b/Qwen3-Embedding-8B-MLX-BF16-oQ8e-s128-l512.npz +3 -0
- calibration/qwen3-embedding-8b/Qwen3-Embedding-8B-MLX-BF16-oQ8e-s128-l512.npz.json +95 -0
- cloud-results/gte-qwen2-1.5b/cuda-bf16-root-pack.json +32 -0
- cloud-results/gte-qwen2-1.5b/cuda-bf16-root-pack.npz +3 -0
- cloud-results/gte-qwen2-1.5b/cuda-bf16.json +38 -0
- cloud-results/gte-qwen2-1.5b/cuda-bf16.npz +3 -0
- cloud-results/gte-qwen2-1.5b/cuda-bnb-int8-corrected-comparison.json +14 -0
- cloud-results/gte-qwen2-1.5b/cuda-bnb-int8.json +53 -0
- cloud-results/gte-qwen2-1.5b/cuda-bnb-int8.npz +3 -0
- cloud-results/gte-qwen2-1.5b/cuda-bnb-nf4.json +53 -0
- cloud-results/gte-qwen2-1.5b/cuda-bnb-nf4.npz +3 -0
- cloud-results/qwen3-embedding-0.6b/cuda-bf16.json +26 -0
- cloud-results/qwen3-embedding-0.6b/cuda-bf16.npz +3 -0
- cloud-results/qwen3-embedding-0.6b/cuda-bnb-int8.json +52 -0
- cloud-results/qwen3-embedding-0.6b/cuda-bnb-int8.npz +3 -0
- cloud-results/qwen3-embedding-0.6b/cuda-bnb-nf4.json +52 -0
- cloud-results/qwen3-embedding-0.6b/cuda-bnb-nf4.npz +3 -0
- cloud-results/qwen3-embedding-8b/cuda-bf16.json +32 -0
- cloud-results/qwen3-embedding-8b/cuda-bf16.npz +3 -0
- cloud-results/qwen3-embedding-8b/cuda-bnb-int8.json +53 -0
- cloud-results/qwen3-embedding-8b/cuda-bnb-int8.npz +3 -0
- cloud-results/qwen3-embedding-8b/cuda-bnb-nf4.json +53 -0
- cloud-results/qwen3-embedding-8b/cuda-bnb-nf4.npz +3 -0
- inputs/retrieval_pairs.json +98 -0
- local-reference/qwen3-embedding-0.6b/bf16.npz +3 -0
- local-results/full-q4-q6-q8/gte-qwen2-1.5b/first-job.json +658 -0
- local-results/full-q4-q6-q8/gte-qwen2-1.5b/quality/bf16.log +45 -0
- local-results/full-q4-q6-q8/gte-qwen2-1.5b/quality/bf16.npz +3 -0
- local-results/full-q4-q6-q8/gte-qwen2-1.5b/quality/compare-oq4.json +115 -0
- local-results/full-q4-q6-q8/gte-qwen2-1.5b/quality/compare-oq4.log +115 -0
- local-results/full-q4-q6-q8/gte-qwen2-1.5b/quality/compare-oq4e.json +115 -0
- local-results/full-q4-q6-q8/gte-qwen2-1.5b/quality/compare-oq4e.log +115 -0
- local-results/full-q4-q6-q8/gte-qwen2-1.5b/quality/compare-oq6.json +115 -0
- local-results/full-q4-q6-q8/gte-qwen2-1.5b/quality/compare-oq6.log +115 -0
- local-results/full-q4-q6-q8/gte-qwen2-1.5b/quality/compare-oq6e.json +115 -0
- local-results/full-q4-q6-q8/gte-qwen2-1.5b/quality/compare-oq6e.log +115 -0
- local-results/full-q4-q6-q8/gte-qwen2-1.5b/quality/compare-oq8.json +115 -0
- local-results/full-q4-q6-q8/gte-qwen2-1.5b/quality/compare-oq8.log +115 -0
- local-results/full-q4-q6-q8/gte-qwen2-1.5b/quality/compare-oq8e.json +115 -0
- local-results/full-q4-q6-q8/gte-qwen2-1.5b/quality/compare-oq8e.log +115 -0
- local-results/full-q4-q6-q8/gte-qwen2-1.5b/quality/compare-q4.json +115 -0
- local-results/full-q4-q6-q8/gte-qwen2-1.5b/quality/compare-q4.log +115 -0
- local-results/full-q4-q6-q8/gte-qwen2-1.5b/quality/compare-q6.json +115 -0
- local-results/full-q4-q6-q8/gte-qwen2-1.5b/quality/compare-q6.log +115 -0
.gitignore
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.venv/
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work/
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__pycache__/
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*.pyc
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README.md
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---
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pretty_name: Embedding Quantization Reproducibility Bundle
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tags:
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- embeddings
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- quantization
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- mlx
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- zerogpu
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- reproducibility
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---
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# Embedding quantization reproducibility bundle
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This dataset contains the frozen inputs, vector artifacts, metrics, calibration
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| 14 |
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evidence, and scripts behind the companion engineering post on MLX Q/oQ/oQe
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| 15 |
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embedding quantization and CUDA-native controls.
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| 16 |
+
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The model weights are not duplicated here. `models.lock.json` pins all 30 public
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model repositories to exact Hub commits and records their canonical upstream
|
| 19 |
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BF16 revisions. Quantized artifacts branch directly from their family's BF16
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checkpoint; no lossy conversion was used as another quantization's source.
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## Verify the published evidence
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| 23 |
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```bash
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hf download TiGa-RCE/embedding-quant-repro-2026-07-28 \
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--repo-type dataset --local-dir embedding-quant-repro
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cd embedding-quant-repro
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uv sync
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uv run reproduce.py verify
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uv run reproduce.py mixed-index
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```
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`verify` checks the locked revisions, bundle checksums, all 30 saved MLX vector
|
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artifacts, and the three-family mixed-index result. `mixed-index` regenerates the
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54 migration-direction measurements from the saved vectors without downloading
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model weights.
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## Local MLX gate on Apple Silicon
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The quick profile downloads the locked 0.6B BF16 and representative Q4/Q6/Q8
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| 41 |
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artifacts, then reproduces their vector comparisons:
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| 42 |
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```bash
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uv sync --extra mlx
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| 45 |
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uv run reproduce.py mlx --profile quick
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| 46 |
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```
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| 47 |
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The complete matrix is intentionally explicit because it downloads all 30
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checkpoints:
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| 50 |
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```bash
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uv run reproduce.py mlx --profile full --family all
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```
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|
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## CUDA controls through ZeroGPU
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| 56 |
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After authenticating with Hugging Face, the client invokes the bounded BF16,
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bitsandbytes INT8, and bitsandbytes NF4 controls:
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| 59 |
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| 60 |
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```bash
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| 61 |
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hf auth login
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uv sync --extra zerogpu
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uv run reproduce.py cuda --family all --variant all
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```
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These bitsandbytes results are controls, not MLX Q/oQ/oQe equivalents. ZeroGPU
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quota and scheduling still apply.
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## Evidence boundaries
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- The frozen set has 24 query/document pairs. This is an engineering smoke test,
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not MTEB or a universal retrieval-quality claim.
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- Q4 remains in the bundle as an intentionally failed fidelity comparator.
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| 74 |
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- GTE-Qwen2 1.5B CUDA vectors are quarantined from MLX cross-runtime trends
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| 75 |
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because that family failed loading-path parity.
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| 76 |
+
- `scripts/frozen-original/` preserves the exact experiment scripts, including
|
| 77 |
+
their historical local paths. Use `reproduce.py` for the portable interface.
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| 78 |
+
- The bundle contains no credentials.
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calibration/gte-qwen2-1.5b/gte-Qwen2-1.5B-instruct-mlx-bf16-oQe-s128-l512.npz
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version https://git-lfs.github.com/spec/v1
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oid sha256:551fe3094b3bd82b1ae32756d1e94f4e0667d3f02cb61d13898a88c5778550c0
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size 1896251
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calibration/gte-qwen2-1.5b/gte-Qwen2-1.5B-instruct-mlx-bf16-oQe-s128-l512.npz.json
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{
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| 2 |
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"format": "omlx-oqe-imatrix-cache",
|
| 3 |
+
"model_name": "gte-Qwen2-1.5B-instruct-mlx-bf16",
|
| 4 |
+
"source_hash": "e9843bef7adfd5996af8b44d50cafd891bd48cb77e00f0c0156d852264b9ba69",
|
| 5 |
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"calib_dataset": "oqe_code_multilingual",
|
| 6 |
+
"calib_data_hash": "04d98e2d7367f7a53e3efa759acded87717d8b70562df142e1e02963af571aa0",
|
| 7 |
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"num_samples": 128,
|
| 8 |
+
"seq_length": 512,
|
| 9 |
+
"entry_count": 196,
|
| 10 |
+
"collection": {
|
| 11 |
+
"dataset": "oqe_code_multilingual",
|
| 12 |
+
"requested_samples": 128,
|
| 13 |
+
"seq_length": 512,
|
| 14 |
+
"adaptive": true,
|
| 15 |
+
"adaptive_step_samples": 128,
|
| 16 |
+
"adaptive_max_samples": 1024,
|
| 17 |
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"available_samples": 1024,
|
| 18 |
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"micro_batch_size": 32,
|
| 19 |
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"micro_batches": 4,
|
| 20 |
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"batch_plan": {
|
| 21 |
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"micro_batch_size": 32,
|
| 22 |
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"estimated_sample_bytes": 3145728,
|
| 23 |
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"capture_budget_bytes": 182312304,
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| 24 |
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"system_available_bytes": 18231230464,
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| 25 |
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"metal_available_bytes": 26796109164,
|
| 26 |
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"live_available_bytes": 18231230464,
|
| 27 |
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"hidden_size": 1536,
|
| 28 |
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"num_experts": 0,
|
| 29 |
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"top_k": 1
|
| 30 |
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},
|
| 31 |
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"processed_samples": 128,
|
| 32 |
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"installed_modules": 197,
|
| 33 |
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"capture_module_classes": {
|
| 34 |
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"Linear": 197
|
| 35 |
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},
|
| 36 |
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"switch_capture_modules": 0,
|
| 37 |
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"requires_expert_counts": false,
|
| 38 |
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"coverage_sufficient": true,
|
| 39 |
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"collection_sufficient": true,
|
| 40 |
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"coverage": {
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| 41 |
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"has_expert_counts": false,
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| 42 |
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"expert_modules": 0,
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"total_experts": 0,
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"active_experts": 0,
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"zero_count_experts": 0,
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"active_ratio": 1.0,
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"min_count": 0,
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"p05_count": 0.0,
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"p10_count": 0.0,
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"median_count": 0.0,
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"max_count": 0,
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"min_required_count": 16,
|
| 53 |
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"required_percentile": 5
|
| 54 |
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},
|
| 55 |
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"rounds": [
|
| 56 |
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{
|
| 57 |
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"processed_samples": 128,
|
| 58 |
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"coverage_sufficient": true,
|
| 59 |
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"collection_sufficient": true,
|
| 60 |
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"coverage": {
|
| 61 |
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"has_expert_counts": false,
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"expert_modules": 0,
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"total_experts": 0,
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"active_experts": 0,
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"zero_count_experts": 0,
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"active_ratio": 1.0,
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"min_count": 0,
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"p05_count": 0.0,
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"p10_count": 0.0,
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"median_count": 0.0,
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"max_count": 0,
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"min_required_count": 16,
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"required_percentile": 5
|
| 74 |
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}
|
| 75 |
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}
|
| 76 |
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]
|
| 77 |
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},
|
| 78 |
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"expert_coverage": {
|
| 79 |
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"has_expert_counts": false,
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"expert_modules": 0,
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"total_experts": 0,
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"active_experts": 0,
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"zero_count_experts": 0,
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"active_ratio": 1.0,
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"min_count": 0,
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"p05_count": 0.0,
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"p10_count": 0.0,
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"median_count": 0.0,
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"max_count": 0,
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"min_required_count": 16,
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"required_percentile": 5
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},
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"requires_expert_counts": false,
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"processed_samples": 128
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| 95 |
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}
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calibration/qwen3-embedding-0.6b/Qwen3-Embedding-0.6B-MLX-BF16-oQe-s128-l512.npz
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version https://git-lfs.github.com/spec/v1
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oid sha256:d4dc104757d90763d249b53d52e00ed8ae47f918cd2dc61c66585659fffcd429
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size 1126602
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calibration/qwen3-embedding-0.6b/Qwen3-Embedding-0.6B-MLX-BF16-oQe-s128-l512.npz.json
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cloud-results/gte-qwen2-1.5b/cuda-bf16.npz
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size 179494
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cloud-results/gte-qwen2-1.5b/cuda-bnb-int8-corrected-comparison.json
ADDED
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| 4 |
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| 14 |
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cloud-results/gte-qwen2-1.5b/cuda-bnb-int8.json
ADDED
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cloud-results/gte-qwen2-1.5b/cuda-bnb-int8.npz
ADDED
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cloud-results/gte-qwen2-1.5b/cuda-bnb-nf4.json
ADDED
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cloud-results/gte-qwen2-1.5b/cuda-bnb-nf4.npz
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cloud-results/qwen3-embedding-0.6b/cuda-bf16.json
ADDED
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cloud-results/qwen3-embedding-0.6b/cuda-bnb-int8.json
ADDED
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}
|
| 53 |
+
}
|
cloud-results/qwen3-embedding-8b/cuda-bnb-nf4.npz
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:539b8d155338a690beed6db108065ea33a97eed2b916d7391081043eced0b55c
|
| 3 |
+
size 623867
|
inputs/retrieval_pairs.json
ADDED
|
@@ -0,0 +1,98 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
[
|
| 2 |
+
{
|
| 3 |
+
"query": "Which city is the capital of France?",
|
| 4 |
+
"document": "Paris is the capital and most populous city of France."
|
| 5 |
+
},
|
| 6 |
+
{
|
| 7 |
+
"query": "What is Canada's national capital rather than its largest city?",
|
| 8 |
+
"document": "Ottawa is the capital of Canada; Toronto is the country's largest city."
|
| 9 |
+
},
|
| 10 |
+
{
|
| 11 |
+
"query": "How do green plants turn light into stored chemical energy?",
|
| 12 |
+
"document": "Photosynthesis uses light energy to convert carbon dioxide and water into sugars and oxygen."
|
| 13 |
+
},
|
| 14 |
+
{
|
| 15 |
+
"query": "Which organelle produces most cellular ATP?",
|
| 16 |
+
"document": "Mitochondria generate most of a eukaryotic cell's ATP through oxidative phosphorylation."
|
| 17 |
+
},
|
| 18 |
+
{
|
| 19 |
+
"query": "What vulnerability occurs when untrusted input changes a database query?",
|
| 20 |
+
"document": "SQL injection happens when attacker-controlled input alters the structure or meaning of a database query."
|
| 21 |
+
},
|
| 22 |
+
{
|
| 23 |
+
"query": "Why must password hashes use a unique random salt?",
|
| 24 |
+
"document": "A unique salt prevents identical passwords from producing identical hashes and defeats precomputed rainbow tables."
|
| 25 |
+
},
|
| 26 |
+
{
|
| 27 |
+
"query": "Which digest can verify that a downloaded file has not changed?",
|
| 28 |
+
"document": "A published SHA-256 digest can be recomputed and compared to detect accidental or malicious file changes."
|
| 29 |
+
},
|
| 30 |
+
{
|
| 31 |
+
"query": "How can I identify the process listening on a local TCP port on macOS?",
|
| 32 |
+
"document": "The lsof command can map a listening TCP port to its owning process and process identifier."
|
| 33 |
+
},
|
| 34 |
+
{
|
| 35 |
+
"query": "How can separate storage roles appear at stable paths on macOS?",
|
| 36 |
+
"document": "Named APFS volumes mount under stable paths such as /Volumes/Models or /Volumes/Labs."
|
| 37 |
+
},
|
| 38 |
+
{
|
| 39 |
+
"query": "What is a small trainable adapter applied over frozen model weights?",
|
| 40 |
+
"document": "LoRA trains low-rank adapter matrices while leaving the base model weights frozen."
|
| 41 |
+
},
|
| 42 |
+
{
|
| 43 |
+
"query": "What reduces model storage by representing weights with fewer bits?",
|
| 44 |
+
"document": "Weight quantization reduces model size and memory use by storing parameters at lower numerical precision."
|
| 45 |
+
},
|
| 46 |
+
{
|
| 47 |
+
"query": "What calibration artifact records activation importance for enhanced quantization?",
|
| 48 |
+
"document": "An importance matrix, or imatrix, summarizes activation statistics used to guide importance-aware quantization."
|
| 49 |
+
},
|
| 50 |
+
{
|
| 51 |
+
"query": "Which file format commonly packages quantized language models for llama.cpp?",
|
| 52 |
+
"document": "GGUF is a model container format widely used by llama.cpp for quantized weights and metadata."
|
| 53 |
+
},
|
| 54 |
+
{
|
| 55 |
+
"query": "What database supports semantic search using dense numerical representations?",
|
| 56 |
+
"document": "A vector database indexes embedding vectors and retrieves items using similarity measures such as cosine similarity."
|
| 57 |
+
},
|
| 58 |
+
{
|
| 59 |
+
"query": "What SQLite feature supports fast lexical search across document text?",
|
| 60 |
+
"document": "SQLite FTS5 provides an inverted full-text index for efficient token and phrase search."
|
| 61 |
+
},
|
| 62 |
+
{
|
| 63 |
+
"query": "What layer translates a natural-language file question into a database query?",
|
| 64 |
+
"document": "A text-to-SQL layer converts a user's natural-language request into constrained SQL for the catalog."
|
| 65 |
+
},
|
| 66 |
+
{
|
| 67 |
+
"query": "What should be checked before deleting a local backup after transfer?",
|
| 68 |
+
"document": "Verify the destination copy with cryptographic checksums before removing the local source."
|
| 69 |
+
},
|
| 70 |
+
{
|
| 71 |
+
"query": "Where should unique locally trained weights be kept when they are not needed online?",
|
| 72 |
+
"document": "Cold storage is appropriate for unique LoRAs and locally produced model weights that must remain recoverable."
|
| 73 |
+
},
|
| 74 |
+
{
|
| 75 |
+
"query": "What establishes the expected hosts, services, and ports before monitoring changes?",
|
| 76 |
+
"document": "A network baseline records normal hosts, listening services, process owners, and port relationships."
|
| 77 |
+
},
|
| 78 |
+
{
|
| 79 |
+
"query": "How can a file type be recognized when its extension is misleading?",
|
| 80 |
+
"document": "File signatures inspect characteristic bytes in the content rather than trusting only the filename extension."
|
| 81 |
+
},
|
| 82 |
+
{
|
| 83 |
+
"query": "Why does model inference compete with ordinary applications for memory on Apple silicon?",
|
| 84 |
+
"document": "Apple silicon uses unified memory, so CPU workloads, applications, and GPU model tensors share the same physical RAM."
|
| 85 |
+
},
|
| 86 |
+
{
|
| 87 |
+
"query": "Why does a normal Linux Docker container not provide native MLX Metal acceleration?",
|
| 88 |
+
"document": "MLX targets Apple's Metal framework on macOS, while a standard Linux container does not expose that native runtime."
|
| 89 |
+
},
|
| 90 |
+
{
|
| 91 |
+
"query": "Which tool efficiently synchronizes changed files without retransmitting everything?",
|
| 92 |
+
"document": "rsync compares source and destination state and transfers only the data needed to synchronize them."
|
| 93 |
+
},
|
| 94 |
+
{
|
| 95 |
+
"query": "How are normalized embedding vectors commonly ranked for semantic retrieval?",
|
| 96 |
+
"document": "Cosine similarity ranks normalized embeddings by their vector alignment, with larger dot products indicating closer meaning."
|
| 97 |
+
}
|
| 98 |
+
]
|
local-reference/qwen3-embedding-0.6b/bf16.npz
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:53600185245677c74939f81226851f35b840bea9476c2354d41e34a74ffc75e0
|
| 3 |
+
size 127938
|
local-results/full-q4-q6-q8/gte-qwen2-1.5b/first-job.json
ADDED
|
@@ -0,0 +1,658 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
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|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
|
|
|
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|
|
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|
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|
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|
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local-results/full-q4-q6-q8/gte-qwen2-1.5b/quality/bf16.log
ADDED
|
@@ -0,0 +1,45 @@
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local-results/full-q4-q6-q8/gte-qwen2-1.5b/quality/compare-oq4.log
ADDED
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@@ -0,0 +1,115 @@
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local-results/full-q4-q6-q8/gte-qwen2-1.5b/quality/compare-oq4e.json
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local-results/full-q4-q6-q8/gte-qwen2-1.5b/quality/compare-oq4e.log
ADDED
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@@ -0,0 +1,115 @@
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|
| 113 |
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}
|
| 114 |
+
}
|
| 115 |
+
}
|
local-results/full-q4-q6-q8/gte-qwen2-1.5b/quality/compare-oq6.json
ADDED
|
@@ -0,0 +1,115 @@
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|
|
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|
|
|
|
|
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|
|
|
|
|
|
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|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
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{
|
| 2 |
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|
| 3 |
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| 4 |
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| 14 |
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| 20 |
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| 21 |
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| 47 |
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| 48 |
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| 89 |
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| 92 |
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| 114 |
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|
| 115 |
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|
local-results/full-q4-q6-q8/gte-qwen2-1.5b/quality/compare-oq6.log
ADDED
|
@@ -0,0 +1,115 @@
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|
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|
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|
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|
|
|
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|
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|
|
|
|
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|
|
|
|
|
|
|
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|
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|
|
|
|
|
|
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|
|
|
|
|
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|
|
|
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|
|
|
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|
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|
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|
| 1 |
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{
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|
local-results/full-q4-q6-q8/gte-qwen2-1.5b/quality/compare-oq6e.json
ADDED
|
@@ -0,0 +1,115 @@
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|
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local-results/full-q4-q6-q8/gte-qwen2-1.5b/quality/compare-oq6e.log
ADDED
|
@@ -0,0 +1,115 @@
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|
local-results/full-q4-q6-q8/gte-qwen2-1.5b/quality/compare-oq8.json
ADDED
|
@@ -0,0 +1,115 @@
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local-results/full-q4-q6-q8/gte-qwen2-1.5b/quality/compare-oq8.log
ADDED
|
@@ -0,0 +1,115 @@
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|
local-results/full-q4-q6-q8/gte-qwen2-1.5b/quality/compare-oq8e.json
ADDED
|
@@ -0,0 +1,115 @@
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| 111 |
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|
| 112 |
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|
| 113 |
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}
|
| 114 |
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}
|
| 115 |
+
}
|
local-results/full-q4-q6-q8/gte-qwen2-1.5b/quality/compare-oq8e.log
ADDED
|
@@ -0,0 +1,115 @@
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|
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|
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|
|
|
|
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|
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|
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|
|
|
|
|
|
|
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|
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|
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|
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|
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|
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|
|
|
|
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|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
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{
|
| 2 |
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|
| 3 |
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| 4 |
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| 48 |
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| 89 |
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| 91 |
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| 92 |
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| 93 |
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| 115 |
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|
local-results/full-q4-q6-q8/gte-qwen2-1.5b/quality/compare-q4.json
ADDED
|
@@ -0,0 +1,115 @@
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|
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|
local-results/full-q4-q6-q8/gte-qwen2-1.5b/quality/compare-q4.log
ADDED
|
@@ -0,0 +1,115 @@
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local-results/full-q4-q6-q8/gte-qwen2-1.5b/quality/compare-q6.json
ADDED
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@@ -0,0 +1,115 @@
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|
local-results/full-q4-q6-q8/gte-qwen2-1.5b/quality/compare-q6.log
ADDED
|
@@ -0,0 +1,115 @@
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