Instructions to use mlfoundations-dev/code-contests-sandboxes-traces-terminus-2_seed_44 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mlfoundations-dev/code-contests-sandboxes-traces-terminus-2_seed_44 with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("mlfoundations-dev/code-contests-sandboxes-traces-terminus-2_seed_44", dtype="auto") - Notebooks
- Google Colab
- Kaggle
code-contests-sandboxes-traces-terminus-2_seed_44
This model is a fine-tuned version of Qwen/Qwen3-8B on the mlfoundations-dev/code-contests-sandboxes-traces-terminus-2 dataset.
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 4e-05
- train_batch_size: 1
- eval_batch_size: 8
- seed: 44
- distributed_type: multi-GPU
- num_devices: 16
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- total_eval_batch_size: 128
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 5.0
Training results
Framework versions
- Transformers 4.55.0
- Pytorch 2.7.0+cu128
- Datasets 3.6.0
- Tokenizers 0.21.1
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