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 2570, 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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| 2578 |
"mean_token_accuracy": 0.7738461554050445,
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"num_tokens": 11895685.0,
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| 2580 |
"step": 2560
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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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| 2601 |
"train_batch_size": 4,
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| 2602 |
"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": 0.5482666666666667,
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"eval_steps": 500,
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"global_step": 2570,
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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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| 2578 |
"mean_token_accuracy": 0.7738461554050445,
|
| 2579 |
"num_tokens": 11895685.0,
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| 2580 |
"step": 2560
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| 2581 |
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},
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| 2582 |
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{
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| 2583 |
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"entropy": 0.8330970570445061,
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| 2584 |
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"epoch": 0.5482666666666667,
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| 2585 |
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"grad_norm": 0.25935855507850647,
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| 2586 |
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"learning_rate": 8.535533905932738e-05,
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| 2587 |
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"loss": 0.9135859489440918,
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| 2588 |
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"mean_token_accuracy": 0.7793566673994065,
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| 2589 |
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"num_tokens": 11940774.0,
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| 2590 |
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"step": 2570
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| 2591 |
}
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| 2592 |
],
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| 2593 |
"logging_steps": 10,
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| 2607 |
"attributes": {}
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}
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},
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| 2610 |
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"total_flos": 5.662076880986419e+16,
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| 2611 |
"train_batch_size": 4,
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"trial_name": null,
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"trial_params": null
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