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 2130, 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": 0.7480149149894715,
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"step": 2120
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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": 4.
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"train_batch_size": 4,
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"best_global_step": null,
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"epoch": 0.4544,
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"global_step": 2130,
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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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| 2138 |
"mean_token_accuracy": 0.7480149149894715,
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"step": 2120
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{
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"entropy": 1.002899456769228,
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"epoch": 0.4544,
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"grad_norm": 0.24397237598896027,
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| 2146 |
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"learning_rate": 9.031000296529336e-05,
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| 2147 |
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"loss": 1.0722038269042968,
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| 2148 |
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"mean_token_accuracy": 0.7499327704310417,
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| 2149 |
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"num_tokens": 9873482.0,
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"step": 2130
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| 2151 |
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],
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"logging_steps": 10,
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"attributes": {}
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"total_flos": 4.685941906788864e+16,
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"train_batch_size": 4,
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