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 3130, 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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"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": 0.7467011958360672,
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"step": 3120
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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": 6.
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| 3161 |
"train_batch_size": 4,
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| 3162 |
"trial_name": null,
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"best_global_step": null,
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| 3138 |
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| 3139 |
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"step": 3120
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| 3142 |
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{
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| 3143 |
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"entropy": 0.850496319681406,
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| 3144 |
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"epoch": 0.6677333333333333,
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| 3145 |
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"grad_norm": 0.37918779253959656,
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| 3146 |
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"learning_rate": 7.788275420728123e-05,
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| 3147 |
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"loss": 0.914525032043457,
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| 3148 |
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"mean_token_accuracy": 0.7852855637669564,
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| 3149 |
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"num_tokens": 14566458.0,
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| 3150 |
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"step": 3130
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| 3151 |
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| 3152 |
],
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| 3153 |
"logging_steps": 10,
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"attributes": {}
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| 3170 |
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"total_flos": 6.897869926043443e+16,
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| 3171 |
"train_batch_size": 4,
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| 3172 |
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