Instructions to use penfever/GLM-4_6-inferredbugs-32eps-65k-fixeps with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use penfever/GLM-4_6-inferredbugs-32eps-65k-fixeps with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("penfever/GLM-4_6-inferredbugs-32eps-65k-fixeps", dtype="auto") - Notebooks
- Google Colab
- Kaggle
GLM-4_6-inferredbugs-32eps-65k-fixeps
This model is a fine-tuned version of Qwen/Qwen3-8B on the penfever/GLM-4.6-inferredbugs-32eps-65k 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: 42
- distributed_type: multi-GPU
- num_devices: 16
- total_train_batch_size: 16
- total_eval_batch_size: 128
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.98) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 7.0
Training results
Framework versions
- Transformers 4.56.0
- Pytorch 2.9.0+cu128
- Datasets 4.4.1
- Tokenizers 0.22.1
- Downloads last month
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