Update README.md

README.md

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 license: mit
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+![IMG_7621](https://github.com/MaxxP0/WorldModel/assets/95175667/525c9f61-7e29-4cbf-8bbd-30421a10f763)
+![IMG_7622](https://github.com/MaxxP0/WorldModel/assets/95175667/58954cb3-78d8-4c32-a0d8-abaad2df0455)
+
+
+# WorldModel
+Note: This was a passion project, crafted in two days. I hope it can be of help to many!
+
+WorldModel is a MaskGIT model trained on 8x8x8 Minecraft voxel volumes. Beyond generating blocks from scratch,
+it excels in filling spaces based on neighboring blocks, ensuring seamless integration in Minecraft worlds
+
+The model weights can be found [here](https://drive.google.com/file/d/1--4Z5VQ-mRQz805yDmJPsPKrIrVCaoCv/view?usp=sharing)
+
+## Prerequisites:
+Ensure your server has the mcpi package installed. This code relies on it to place blocks.
+
+## Functionality:
+This tool uses a special mask token, designated as 831. When you provide a tensor of shape [1,512] containing
+block values ranging from 0-831(including the mask token), the generate function will intelligently fill in
+the masked areas until none remain.
+
+
+## Sampling Strategy Adjustments to maskGIT:
+In contrast to the original maskGIT, sampling solely from the most confident tokens can lead to mode collapse, often
+resulting in generating only stones or air. To address this, I've introduced a random sampling strategy. In the early
+sampling phases, the confidence of potential tokens is disregarded, and tokens are selected for unmasking at random.
+
+You can fine-tune this behavior using the "random_steps" variable. It's crucial to strike a balance between "random_steps"
+and other parameters such as the total "timesteps", "temperature", and "topk_filter_thres".