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@@ -43,7 +43,7 @@ The model outputs two vectors:
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  1. **Policy**: A probability distribution over `NUM_POSSIBLE_MOVES=4672` representing the probability of making each move, obtained using `softmax` activation.
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  2. **Value**: A single scalar value indicating win/loss probability from current player’s perspective, ranging from -1 (loss) to 1 (win), obtained using `tanh` activation.
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- [![StockZero Demo Gameplay Video](https://huggingface.co/nirajandhakal/StockZero/blob/main/demo_video_thumbnail.png)](https://huggingface.co/nirajandhakal/StockZero/blob/main/v2-gameplay-svg-high-quality.mp4)
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  ### Model Architecture
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  These scores indicate that the model, in its current state, is not a strong chess player. It draws a majority of games against a random opponent, but also loses a significant number. Further training and architecture improvements are needed to enhance its performance.
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  ## How to Use
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  ### Training
 
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  1. **Policy**: A probability distribution over `NUM_POSSIBLE_MOVES=4672` representing the probability of making each move, obtained using `softmax` activation.
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  2. **Value**: A single scalar value indicating win/loss probability from current player’s perspective, ranging from -1 (loss) to 1 (win), obtained using `tanh` activation.
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  ### Model Architecture
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  These scores indicate that the model, in its current state, is not a strong chess player. It draws a majority of games against a random opponent, but also loses a significant number. Further training and architecture improvements are needed to enhance its performance.
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+ ## Demo Game Video
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+ You can see a demo game here: [StockZero Demo Gameplay Video](https://huggingface.co/nirajandhakal/StockZero/blob/main/v2-gameplay-svg-high-quality.mp4)
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  ## How to Use
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  ### Training