Transformers
ONNX
Safetensors
English
chess
move-prediction
neural-network
deep-learning
skill-conditioning
player-modeling
Instructions to use peargentlabs/otter-chess with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use peargentlabs/otter-chess with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("peargentlabs/otter-chess", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "step": 1005000, | |
| "val_metrics": { | |
| "loss": 1.5821013190746307, | |
| "acc": 0.54763525390625, | |
| "top5_acc": 0.90795068359375, | |
| "elo_bucket_acc": [ | |
| 0.4907628128724672, | |
| 0.5278608785485225, | |
| 0.5364165398681295, | |
| 0.5444673022019639, | |
| 0.5461964773762527, | |
| 0.5409395058995794, | |
| 0.5537597115825775, | |
| 0.5560619536315501, | |
| 0.5616614631676652, | |
| 0.5509333333333334, | |
| 0.5480438643659057 | |
| ], | |
| "time_bucket_acc": [ | |
| null, | |
| null, | |
| 0.5343344829091544, | |
| 0.5479396020149976, | |
| null | |
| ] | |
| }, | |
| "best_val_acc": 0.54763525390625 | |
| } |