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mnist-conditional-gan
andreribeiro87/mnist-conditional-gan
mnist-conditional-gan is a machine learning model from andreribeiro87. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for pytorch.
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Public
Updated Mar 25, 2026
Repo size
15.4 MB
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Repo makeup
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.pth15.4 MB · 100%
At a glance
- Library
- pytorch
- Access
- Public
- Created
- Mar 25, 2026
- Updated
- Mar 25, 2026
- SHA
- 2f34aadb
Model card
From the Hugging Face model README
mnist-conditional-gan
Local run name: gan_run
Generator weights exported from the Week 6 GAN lab training codebase.
Repository files
| Key | Value |
|---|---|
mnist_cgan_generator.pth | Generator state_dict (PyTorch) |
generator_training_config.json | Training hyperparameters / layout (JSON) |
README.md | This model card (auto-generated on upload) |
Export provenance
| Key | Value |
|---|---|
| Checkpoint path | /home/ucloud/caa-andre/complements-ml-labs-andreribeiro87/week-06/outputs/runs/gan_run__20260322T142324Z__9e0ad9f4/checkpoints/latest.pt |
| Run directory JSON | config.json, run_meta.json |
Run metadata (run_meta.json)
| Key | Value |
|---|---|
| config_fingerprint | 9e0ad9f4 |
| created_utc | 20260322T142324Z |
| run_name | gan_run |
Training configuration (summary)
| Key | Value |
|---|---|
| run_name | gan_run |
| task | mnist |
| image_size | 64 |
| nz | 100 |
| ngf | 64 |
| ndf | 64 |
| num_classes | 10 |
| adversarial_loss | hinge |
| use_gradient_penalty | False |
| lambda_fm | 0.0 |
| lambda_perc | 0.0 |
| epochs | 25 |
| max_steps | None |
| batch_size | 32 |
| lr_g | 0.0002 |
| lr_d | 0.0002 |
| n_critic | 1 |
| seed | 42 |
| spectral_norm_d | True |
Source JSON (run directory)
Verbatim JSON files from the run folder root (next to checkpoints/).
config.json
{
"adversarial_loss": "hinge",
"batch_size": 32,
"beta1": 0.5,
"beta2": 0.999,
"checkpoint_every": 1000,
"data_cache_dir": null,
"device": "cuda",
"epochs": 25,
"eval_at_end": true,
"eval_batch_size": 32,
"eval_every": 1000,
"eval_num_fake": 2048,
"eval_num_real": 2048,
"image_size": 64,
"lambda_fm": 0.0,
"lambda_gp": 10.0,
"lambda_perc": 0.0,
"log_every": 50,
"lr_d": 0.0002,
"lr_g": 0.0002,
"max_steps": null,
"metrics_device": null,
"n_critic": 1,
"n_samples_grid": 64,
"ndf": 64,
"ngf": 64,
"num_classes": 10,
"num_workers": 2,
"nz": 100,
"output_root": "outputs",
"run_name": "gan_run",
"sample_every": 500,
"seed": 42,
"spectral_norm_d": true,
"tags": {},
"task": "mnist",
"use_bf16": true,
"use_gradient_penalty": false,
"use_wandb": true,
"wandb_entity": null,
"wandb_mode": "online",
"wandb_project": "week06-gan"
}
run_meta.json
{
"config": {
"adversarial_loss": "hinge",
"batch_size": 32,
"beta1": 0.5,
"beta2": 0.999,
"checkpoint_every": 1000,
"data_cache_dir": null,
"device": "cuda",
"epochs": 25,
"eval_at_end": true,
"eval_batch_size": 32,
"eval_every": 1000,
"eval_num_fake": 2048,
"eval_num_real": 2048,
"image_size": 64,
"lambda_fm": 0.0,
"lambda_gp": 10.0,
"lambda_perc": 0.0,
"log_every": 50,
"lr_d": 0.0002,
"lr_g": 0.0002,
"max_steps": null,
"metrics_device": null,
"n_critic": 1,
"n_samples_grid": 64,
"ndf": 64,
"ngf": 64,
"num_classes": 10,
"num_workers": 2,
"nz": 100,
"output_root": "outputs",
"run_name": "gan_run",
"sample_every": 500,
"seed": 42,
"spectral_norm_d": true,
"tags": {},
"task": "mnist",
"use_bf16": true,
"use_gradient_penalty": false,
"use_wandb": true,
"wandb_entity": null,
"wandb_mode": "online",
"wandb_project": "week06-gan"
},
"config_fingerprint": "9e0ad9f4",
"created_utc": "20260322T142324Z",
"run_name": "gan_run"
}
- Library
- pytorch
- Languages
- en
- Created
- Mar 25, 2026
- Updated
- Mar 25, 2026