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 4120, 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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| 4128 |
"mean_token_accuracy": 0.7953767567873001,
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"num_tokens": 19155980.0,
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"step": 4110
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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": 9.
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| 4151 |
"train_batch_size": 4,
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| 4152 |
"trial_name": null,
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"best_global_step": null,
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"epoch": 0.8789333333333333,
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"global_step": 4120,
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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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| 4128 |
"mean_token_accuracy": 0.7953767567873001,
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| 4129 |
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| 4130 |
"step": 4110
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| 4132 |
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{
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| 4133 |
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"entropy": 1.0650635436177254,
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| 4134 |
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"epoch": 0.8789333333333333,
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| 4135 |
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"grad_norm": 0.22809672355651855,
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| 4136 |
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"learning_rate": 6.23157722113219e-05,
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| 4137 |
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"loss": 1.208934211730957,
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| 4138 |
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"mean_token_accuracy": 0.7424666874110699,
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| 4139 |
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"num_tokens": 19206121.0,
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| 4140 |
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"step": 4120
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| 4141 |
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| 4142 |
],
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| 4143 |
"logging_steps": 10,
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"attributes": {}
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}
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"total_flos": 9.08747825015808e+16,
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| 4161 |
"train_batch_size": 4,
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| 4162 |
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