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 2620, 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": 0.7750694006681442,
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"num_tokens": 12125503.0,
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"step": 2610
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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": 5.
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| 2651 |
"train_batch_size": 4,
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| 2652 |
"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": 0.5589333333333333,
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"eval_steps": 500,
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"global_step": 2620,
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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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| 2628 |
"mean_token_accuracy": 0.7750694006681442,
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| 2629 |
"num_tokens": 12125503.0,
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| 2630 |
"step": 2610
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| 2631 |
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},
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| 2632 |
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{
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| 2633 |
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"entropy": 0.9893216907978057,
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| 2634 |
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"epoch": 0.5589333333333333,
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| 2635 |
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"grad_norm": 0.2604218125343323,
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| 2636 |
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"learning_rate": 8.47381746991739e-05,
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| 2637 |
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"loss": 1.040914249420166,
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| 2638 |
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"mean_token_accuracy": 0.7624668940901757,
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| 2639 |
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"num_tokens": 12177100.0,
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| 2640 |
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"step": 2620
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| 2641 |
}
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| 2642 |
],
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| 2643 |
"logging_steps": 10,
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| 2657 |
"attributes": {}
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}
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| 2660 |
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"total_flos": 5.77057617504983e+16,
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| 2661 |
"train_batch_size": 4,
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"trial_name": null,
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