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Fix(notebooks,#22395): 3.9 — retirer les renvois morts 3.9f (absorbés dans 3.9e) #23646

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myia-ai-01 merged 2 commits into from
Oct 31, 2026
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Fix(notebooks,#22395): 3.9 — retirer les renvois morts 3.9f (absorbés dans 3.9e) #23646

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Fix(notebooks,#22395): 3.9 -- retirer les renvois morts 3.9f (absorbé…
jsboige Oct 31, 2026
ccde184
Merge branch 'main' into fix/dsa-39-39f-ref
jsboige Oct 31, 2026
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4 changes: 2 additions & 2 deletions ...Notebooks/ML/DataScienceWithAgents/03-Deep-Learning/3.9-Compression-Quantization-FP.ipynb
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"source": [
"# 3.9 — Quantization from scratch : du flottant réduit à l'entier\n",
"**Navigation** : [<< 3.8-Représentations contrastives](3.8-Representations-Contrastives.ipynb) · [Feuille de route de la série](README.md) · [3.10 — Le pendant SOTA diffusion >>](3.10-Modeles-Generatifs-Diffusion-SOTA.ipynb)\n",
"**Compléments** : [3.9b — élagage from scratch (ResNet-20/CIFAR-10)](3.9b-Compression-Pruning-from-scratch.ipynb) · [3.9c — élagage from scratch (MLP/MNIST)](3.9c-Pruning-From-Scratch.ipynb) · [3.7 — Distillation maître-élève](3.7-Distillation-Maitre-Eleve.ipynb) · [3.9e — Quantization SOTA (torch.ao)](3.9e-Compression-SOTA.ipynb) · [3.9f — Pruning SOTA (torch.nn.utils.prune)](_archive/3.9f-Compression-Pruning-SOTA.ipynb) · [3.9g — Comparatif A vs B](3.9g-Compression-Comparatif-A-vs-B.ipynb)\n",
"**Compléments** : [3.9b — élagage from scratch (ResNet-20/CIFAR-10)](3.9b-Compression-Pruning-from-scratch.ipynb) · [3.9c — élagage from scratch (MLP/MNIST)](3.9c-Pruning-From-Scratch.ipynb) · [3.7 — Distillation maître-élève](3.7-Distillation-Maitre-Eleve.ipynb) · [3.9e — Quantization SOTA (torch.ao)](3.9e-Compression-SOTA.ipynb) · [3.9g — Comparatif A vs B](3.9g-Compression-Comparatif-A-vs-B.ipynb)\n",
"\n",
"Le dépôt parle de compression de modèles de façon **incidente** : la quantification apparaît\n",
"dans LoRA (FT-02), le moyennage de poids dans FT-04, la distillation dans 3.7. Il manque le\n",
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"| A.2 | **3.9, partie II** (ce carnet) | INT8 dynamic et static, scale + zero-point, calibration KL, INT4 | livré |\n",
"| A.3 | `3.9b` / `3.9c` | élagage from scratch : magnitude non structuré, filtres structurés, LTH | livré |\n",
"| A.4 | `3.7` | distillation teacher/student, ResNet-20 → ResNet-8 sur CIFAR-10 | livré |\n",
"| B.2 | `3.9e` / `3.9f` | les mêmes techniques par l'écosystème PyTorch (`torch.ao.quantization`, `torch.nn.utils.prune`) | livré |\n",
"| B.2 | `3.9e` | les mêmes techniques par l'écosystème PyTorch (`torch.ao.quantization`, `torch.nn.utils.prune`) | livré |\n",
"| 7 | `3.9g` | comparatif capstone A vs B (accuracy, taille brute + zlib, latence CPU, FLOPs, LOC) | livré |"
]
},
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