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 3520, 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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| 3528 |
"mean_token_accuracy": 0.7408729113638401,
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"num_tokens": 16355489.0,
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| 3530 |
"step": 3510
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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": 7.
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| 3551 |
"train_batch_size": 4,
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| 3552 |
"trial_name": null,
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| 3553 |
"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": 0.7509333333333333,
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"eval_steps": 500,
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"global_step": 3520,
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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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| 3528 |
"mean_token_accuracy": 0.7408729113638401,
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| 3529 |
"num_tokens": 16355489.0,
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| 3530 |
"step": 3510
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| 3531 |
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},
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| 3532 |
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{
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| 3533 |
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"entropy": 0.9718878209590912,
|
| 3534 |
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"epoch": 0.7509333333333333,
|
| 3535 |
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"grad_norm": 0.3055277168750763,
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| 3536 |
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"learning_rate": 7.20432628121669e-05,
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| 3537 |
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"loss": 1.1054911613464355,
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| 3538 |
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"mean_token_accuracy": 0.7583063259720803,
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| 3539 |
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"num_tokens": 16400826.0,
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| 3540 |
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"step": 3520
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| 3541 |
}
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| 3542 |
],
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| 3543 |
"logging_steps": 10,
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| 3557 |
"attributes": {}
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| 3558 |
}
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| 3559 |
},
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| 3560 |
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"total_flos": 7.770614434527744e+16,
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| 3561 |
"train_batch_size": 4,
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| 3562 |
"trial_name": null,
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| 3563 |
"trial_params": null
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