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 3760, 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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| 3768 |
"mean_token_accuracy": 0.7524963855743408,
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"num_tokens": 17474234.0,
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| 3770 |
"step": 3750
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}
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],
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| 3773 |
"logging_steps": 10,
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"attributes": {}
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}
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},
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"total_flos": 8.
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| 3791 |
"train_batch_size": 4,
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| 3792 |
"trial_name": null,
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| 3793 |
"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": 0.8021333333333334,
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"eval_steps": 500,
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"global_step": 3760,
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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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| 3768 |
"mean_token_accuracy": 0.7524963855743408,
|
| 3769 |
"num_tokens": 17474234.0,
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| 3770 |
"step": 3750
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| 3771 |
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},
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| 3772 |
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{
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| 3773 |
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"entropy": 0.9401593998074531,
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| 3774 |
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"epoch": 0.8021333333333334,
|
| 3775 |
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"grad_norm": 0.2025330811738968,
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| 3776 |
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"learning_rate": 6.82432662762483e-05,
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| 3777 |
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"loss": 1.0459843635559083,
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| 3778 |
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"mean_token_accuracy": 0.7684256717562675,
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| 3779 |
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"num_tokens": 17519106.0,
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| 3780 |
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"step": 3760
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| 3781 |
}
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| 3782 |
],
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| 3783 |
"logging_steps": 10,
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| 3797 |
"attributes": {}
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| 3798 |
}
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| 3799 |
},
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| 3800 |
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"total_flos": 8.29500696186962e+16,
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| 3801 |
"train_batch_size": 4,
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| 3802 |
"trial_name": null,
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| 3803 |
"trial_params": null
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