Instructions to use LLM-course/chess_MaximeMuh with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use LLM-course/chess_MaximeMuh with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("LLM-course/chess_MaximeMuh", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 481 Bytes
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library_name: transformers
tags:
- chess
- llm-course
- chess-challenge
license: mit
---
# chess_MaximeMuh
Chess model submitted to the LLM Course Chess Challenge.
## Submission Info
- **Submitted by**: [MaximeMuhlethaler](https://huggingface.co/MaximeMuhlethaler)
- **Parameters**: 980,000
- **Organization**: LLM-course
- **Architecture**: Custom Chess Transformer (Regex Tokenizer + EOS Protection)
## Model Details
- **Vocab size**: 1700
- **Layers**: 6
- **Heads**: 8
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