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 3470, 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": 0.7672612771391869,
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"num_tokens": 16128753.0,
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"step": 3460
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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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| 3501 |
"train_batch_size": 4,
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"trial_name": null,
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| 3503 |
"trial_params": null
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"best_global_step": null,
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"epoch": 0.7402666666666666,
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"global_step": 3470,
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"is_world_process_zero": true,
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| 3478 |
"mean_token_accuracy": 0.7672612771391869,
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| 3479 |
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| 3480 |
"step": 3460
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| 3481 |
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| 3482 |
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{
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| 3483 |
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"entropy": 0.9178998105227947,
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| 3484 |
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"epoch": 0.7402666666666666,
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| 3485 |
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"grad_norm": 0.24847134947776794,
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| 3486 |
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"learning_rate": 7.281664421551684e-05,
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| 3487 |
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"loss": 1.0369275093078614,
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| 3488 |
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"mean_token_accuracy": 0.7686163082718849,
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| 3489 |
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"num_tokens": 16169199.0,
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| 3490 |
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"step": 3470
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| 3491 |
}
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| 3492 |
],
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| 3493 |
"logging_steps": 10,
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| 3507 |
"attributes": {}
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}
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| 3509 |
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| 3510 |
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"total_flos": 7.657711040244326e+16,
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| 3511 |
"train_batch_size": 4,
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| 3512 |
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| 3513 |
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