Instructions to use moos124/code-reasoning-0.5b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use moos124/code-reasoning-0.5b with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("moos124/code-reasoning-0.5b", dtype="auto") - Notebooks
- Google Colab
- Kaggle
Training in progress, step 2430, checkpoint
Browse files
last-checkpoint/adapter_model.safetensors
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last-checkpoint/optimizer.pt
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last-checkpoint/rng_state.pth
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last-checkpoint/scheduler.pt
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last-checkpoint/trainer_state.json
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"best_global_step": null,
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"best_metric": null,
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"best_model_checkpoint": null,
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"epoch": 0.
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"eval_steps": 500,
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"global_step":
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"is_hyper_param_search": false,
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"is_local_process_zero": true,
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"is_world_process_zero": true,
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| 2438 |
"mean_token_accuracy": 0.7819159016013145,
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"num_tokens": 11257215.0,
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"step": 2420
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}
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],
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"logging_steps": 10,
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"attributes": {}
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}
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},
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"total_flos": 5.
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| 2461 |
"train_batch_size": 4,
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| 2462 |
"trial_name": null,
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"trial_params": null
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"best_global_step": null,
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"best_metric": null,
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"best_model_checkpoint": null,
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"epoch": 0.5184,
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"eval_steps": 500,
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"global_step": 2430,
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"is_hyper_param_search": false,
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"is_local_process_zero": true,
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"is_world_process_zero": true,
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| 2438 |
"mean_token_accuracy": 0.7819159016013145,
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| 2439 |
"num_tokens": 11257215.0,
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| 2440 |
"step": 2420
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| 2441 |
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| 2442 |
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{
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| 2443 |
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"entropy": 1.030208633840084,
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| 2444 |
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"epoch": 0.5184,
|
| 2445 |
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"grad_norm": 0.34487199783325195,
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| 2446 |
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"learning_rate": 8.702648271265559e-05,
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| 2447 |
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"loss": 1.1172332763671875,
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| 2448 |
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"mean_token_accuracy": 0.7529917880892754,
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| 2449 |
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"num_tokens": 11302807.0,
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| 2450 |
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"step": 2430
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| 2451 |
}
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| 2452 |
],
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| 2453 |
"logging_steps": 10,
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| 2467 |
"attributes": {}
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}
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},
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| 2470 |
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"total_flos": 5.360216229135974e+16,
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| 2471 |
"train_batch_size": 4,
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| 2472 |
"trial_name": null,
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| 2473 |
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