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 2560, 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": 0.7507105216383934,
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"num_tokens": 11847802.0,
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| 2570 |
"step": 2550
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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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"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": 0.5461333333333334,
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"eval_steps": 500,
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"global_step": 2560,
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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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| 2568 |
"mean_token_accuracy": 0.7507105216383934,
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| 2569 |
"num_tokens": 11847802.0,
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| 2570 |
"step": 2550
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| 2571 |
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| 2572 |
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{
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| 2573 |
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"entropy": 0.9052864700555802,
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| 2574 |
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"epoch": 0.5461333333333334,
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| 2575 |
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"grad_norm": 0.21368557214736938,
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| 2576 |
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"learning_rate": 8.54775069943376e-05,
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| 2577 |
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"loss": 0.9432812690734863,
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| 2578 |
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"mean_token_accuracy": 0.7738461554050445,
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| 2579 |
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"num_tokens": 11895685.0,
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| 2580 |
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"step": 2560
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| 2581 |
}
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| 2582 |
],
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| 2583 |
"logging_steps": 10,
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| 2597 |
"attributes": {}
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}
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},
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"total_flos": 5.642576098367078e+16,
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| 2601 |
"train_batch_size": 4,
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"trial_name": null,
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