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 3860, 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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| 3868 |
"mean_token_accuracy": 0.7734792202711105,
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"num_tokens": 17939963.0,
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| 3870 |
"step": 3850
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}
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],
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| 3873 |
"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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| 3891 |
"train_batch_size": 4,
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| 3892 |
"trial_name": null,
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| 3893 |
"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": 0.8234666666666667,
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"eval_steps": 500,
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"global_step": 3860,
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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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| 3868 |
"mean_token_accuracy": 0.7734792202711105,
|
| 3869 |
"num_tokens": 17939963.0,
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| 3870 |
"step": 3850
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| 3871 |
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},
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| 3872 |
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{
|
| 3873 |
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"entropy": 0.985682574659586,
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| 3874 |
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"epoch": 0.8234666666666667,
|
| 3875 |
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"grad_norm": 0.26758262515068054,
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| 3876 |
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"learning_rate": 6.662126064136466e-05,
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| 3877 |
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"loss": 1.073539638519287,
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| 3878 |
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"mean_token_accuracy": 0.7554293870925903,
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| 3879 |
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"num_tokens": 17990860.0,
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| 3880 |
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"step": 3860
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| 3881 |
}
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| 3882 |
],
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| 3883 |
"logging_steps": 10,
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| 3897 |
"attributes": {}
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}
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| 3899 |
},
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| 3900 |
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"total_flos": 8.518950095995085e+16,
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| 3901 |
"train_batch_size": 4,
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| 3902 |
"trial_name": null,
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| 3903 |
"trial_params": null
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