Instructions to use yashash045/devops-pipeline-gym-trained with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use yashash045/devops-pipeline-gym-trained with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("yashash045/devops-pipeline-gym-trained", dtype="auto") - Notebooks
- Google Colab
- Kaggle
Phase M Stage 2: GRPO 200 steps adapter + training logs (logs/, grpo_log.csv, curriculum_progress.jsonl, reward_curve.png)
326213b verified - Xet hash:
- dde3c5a4d468da6fe61f11ffa8f04af2d101f8f4a0fe118c37bd31bb8c3017b6
- Size of remote file:
- 11.4 MB
- SHA256:
- be75606093db2094d7cd20f3c2f385c212750648bd6ea4fb2bf507a6a4c55506
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