LLM-course / chess_good_but_inefficient

huggingface.co
Total runs: 21
24-hour runs: 0
7-day runs: 0
30-day runs: 4
Model's Last Updated: January 19 2026
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Introduction of chess_good_but_inefficient

Model Details of chess_good_but_inefficient

chess_good_but_inefficient

Chess model submitted to the LLM Course Chess Challenge.

Submission Info
  • Submitted by : Dhia-GB
  • Parameters : 997,248
  • Organization : LLM-course
Model Details
  • Architecture : Chess Transformer (GPT-style)
  • Vocab size : 85
  • Embedding dim : 128
  • Layers : 6
  • Heads : 4

Runs of LLM-course chess_good_but_inefficient on huggingface.co

21
Total runs
0
24-hour runs
0
3-day runs
0
7-day runs
4
30-day runs

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chess_good_but_inefficient huggingface.co

chess_good_but_inefficient huggingface.co is an AI model on huggingface.co that provides chess_good_but_inefficient's model effect (), which can be used instantly with this LLM-course chess_good_but_inefficient model. huggingface.co supports a free trial of the chess_good_but_inefficient model, and also provides paid use of the chess_good_but_inefficient. Support call chess_good_but_inefficient model through api, including Node.js, Python, http.

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LLM-course chess_good_but_inefficient online free url in huggingface.co:

https://huggingface.co/LLM-course/chess_good_but_inefficient

chess_good_but_inefficient install

chess_good_but_inefficient is an open source model from GitHub that offers a free installation service, and any user can find chess_good_but_inefficient on GitHub to install. At the same time, huggingface.co provides the effect of chess_good_but_inefficient install, users can directly use chess_good_but_inefficient installed effect in huggingface.co for debugging and trial. It also supports api for free installation.

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https://huggingface.co/LLM-course/chess_good_but_inefficient

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Growth Rate: 50.00%
Updated:January 18 2026
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