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 3380, 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": 0.7839296951889991,
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"num_tokens": 15691801.0,
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"step": 3370
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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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"train_batch_size": 4,
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"trial_name": null,
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"best_global_step": null,
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"epoch": 0.7210666666666666,
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"global_step": 3380,
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"is_world_process_zero": true,
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| 3388 |
"mean_token_accuracy": 0.7839296951889991,
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| 3389 |
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"step": 3370
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{
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| 3393 |
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"entropy": 0.9314685501158237,
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| 3394 |
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"epoch": 0.7210666666666666,
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| 3395 |
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"grad_norm": 0.2979079782962799,
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| 3396 |
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"learning_rate": 7.419135403371976e-05,
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| 3397 |
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"loss": 1.051080322265625,
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| 3398 |
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"mean_token_accuracy": 0.7620216578245163,
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| 3399 |
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"num_tokens": 15736780.0,
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| 3400 |
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"step": 3380
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| 3401 |
}
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],
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"logging_steps": 10,
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"attributes": {}
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}
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"total_flos": 7.454063535555072e+16,
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"train_batch_size": 4,
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