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 2790, 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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"mean_token_accuracy": 0.7723072916269302,
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"num_tokens": 12921599.0,
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"step": 2780
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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": 6.
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"train_batch_size": 4,
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"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": 0.5952,
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"eval_steps": 500,
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"global_step": 2790,
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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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| 2798 |
"mean_token_accuracy": 0.7723072916269302,
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| 2799 |
"num_tokens": 12921599.0,
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| 2800 |
"step": 2780
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| 2801 |
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{
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| 2803 |
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"entropy": 0.9700805857777596,
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| 2804 |
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"epoch": 0.5952,
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| 2805 |
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"grad_norm": 0.27477312088012695,
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| 2806 |
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"learning_rate": 8.256311685229085e-05,
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| 2807 |
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"loss": 1.1071263313293458,
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| 2808 |
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"mean_token_accuracy": 0.7538750320672989,
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| 2809 |
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"num_tokens": 12969810.0,
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| 2810 |
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"step": 2790
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| 2811 |
}
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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": 6.147365107786752e+16,
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"train_batch_size": 4,
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"trial_name": null,
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