Upload folder using huggingface_hub

qSSL/README.md

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+# Quantum Self-Supervised Learning (qSSL)
+
+This directory gathers the pretrained checkpoints produced while reproducing “Quantum Self-Supervised Learning” (Jaderberg et al., 2021) — https://arxiv.org/abs/2103.14653.  
+Each backend (photonic MerLin, Qiskit gate-based, and the classical MLP baseline) lives in its own subfolder and contains the per-epoch `.pth` weights, the resolved training arguments (`args.json`), and the saved metrics for the corresponding run timestamp.
+
+## Where to fetch the weights
+- Hugging Face repository: `Quandela/ReproducedPapersQML`
+- Layout on the Hub: `qSSL/<backend>/<timestamp>/...`
+  - Example: `qSSL/merlin/20250827_181840/model-cl-5-epoch-5.pth`
+  - The Qiskit checkpoints were obtained with the authors’ original gate-model workflow from https://arxiv.org/abs/2103.14653.
+
+You can inspect the latest timestamps and files directly on the Hub page or by calling the Hub API.
+
+## Loading a checkpoint in Python
+
+Install the tooling (if not already available):
+
+```bash
+pip install huggingface_hub torch
+```
+
+Download the artifacts for a given run and load the state dictionary:
+
+```python
+from argparse import Namespace
+from pathlib import Path
+import json
+import torch
+from huggingface_hub import snapshot_download
+
+run_id = "qSSL/merlin/20250827_181840"
+local_root = Path(
+    snapshot_download(
+        repo_id="Quandela/ReproducedPapersQML",
+        repo_type="model",
+        allow_patterns=[f"{run_id}/*"],
+    )
+)
+
+args_path = local_root / run_id / "args.json"
+state_path = local_root / run_id / "model-cl-5-epoch-5.pth"
+
+args = Namespace(**json.loads(args_path.read_text()))
+state_dict = torch.load(state_path, map_location="cpu")
+```
+
+Rebuild the PyTorch model before loading the weights. If you are using the reproduction codebase (see below), instantiate the `QSSL` model with the `args` namespace and load the weights:
+
+```python
+import sys
+
+repo_root = Path("/path/to/reproduced_papers")  # adjust to your clone
+sys.path.append(str(repo_root / "qSSL"))
+
+from lib.model import QSSL
+
+model = QSSL(args)
+model.load_state_dict(state_dict)
+model.eval()
+```
+
+- For MerLin runs you will need `merlin` and `perceval`.
+- For Qiskit runs install the dependencies from the paper’s reference implementation (`qiskit`, `qiskit-aer`, etc.). These checkpoints were generated with the same circuit and training recipe as the authors’ code: https://arxiv.org/abs/2103.14653.
+
+## More background
+
+You can find a full description of the experiments, configuration options, and evaluation protocol in `reproduced_papers/qSSL/README.md` of the main reproduction repository (`fork_reproduced_papers`). It documents dataset preparation, training/linear-probing scripts, and the differences between the MerLin, Qiskit, and classical variants.

qSSL/classical/20250820_074948/args.json

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+{
+    "datadir": "./data",
+    "classes": 5,
+    "epochs": 5,
+    "le_epochs": 100,
+    "batch_size": 128,
+    "ckpt_step": 1,
+    "batch_norm": false,
+    "loss_dim": 128,
+    "temperature": 0.07,
+    "width": 8,
+    "merlin": false,
+    "modes": 10,
+    "no_bunching": false,
+    "qiskit": false,
+    "layers": 2,
+    "q_backend": "qasm_simulator",
+    "encoding": "vector",
+    "q_ansatz": "sim_circ_14_half",
+    "q_sweeps": 1,
+    "activation": "null",
+    "shots": 100,
+    "save_dhs": false
+}

qSSL/classical/20250820_074948/linear_probing_results_20250822_105654.json

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+{
+  "timestamp": "2025-08-22T10:56:54.495487",
+  "experiment_type": "Linear_Probing",
+  "pretrained_epoch": 4,
+  "arguments": {
+    "datadir": "./data",
+    "classes": 5,
+    "epochs": 5,
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+    "merlin": false,
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+    "encoding": "vector",
+    "q_ansatz": "sim_circ_14_half",
+    "q_sweeps": 1,
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qSSL/classical/20250820_074948/linear_probing_results_20250822_124823.json

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qSSL/classical/20250820_074948/linear_probing_results_20250822_142207.json

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qSSL/classical/20250820_074948/linear_probing_results_20250822_155515.json

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qSSL/classical/20250820_074948/linear_probing_results_20250822_172846.json

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qSSL/merlin/20250827_181840/linear_probing_results_20250828_221846.json

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qSSL/qiskit/20250824_084821/args.json

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qSSL/qiskit/20250824_084821/linear_probing_results_20250828_152550.json

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