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  # Multimodal Classification Model (BM-v1)
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- This model combines text and image inputs to perform classification tasks using a ResNet50 backbone for image processing and a text encoder for textual input processing.
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  ## Model Details
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  - **Model type:** Multimodal Classification Model
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  - **Language(s):** English
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  - **License:** MIT
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- - **Parent Model:** ResNet50 (for image processing)
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  ## Uses
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  ### Direct Use
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- The model is designed for multimodal classification tasks that require both image and text inputs. Example usage:
 
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  # Multimodal Classification Model (BM-v1)
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+ This model combines text and image inputs to predict player moves from in-game screenshots for the popular 4X Civilization VI. In use, screenshot inputs are provided and text inputs generated using an LLM.
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  ## Model Details
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  - **Model type:** Multimodal Classification Model
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  - **Language(s):** English
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  - **License:** MIT
 
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  ## Uses
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+ Predicts the likely moves a player will make from a complete sample space of all (observed) player moves, based on a provided screenshot and associated text. Can be fine-tuned to specifically predict types of move (scouting, build orders, settle/doesn't settle)
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  ### Direct Use
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+ Predicts the likely moves a player will make, from a complete sample space of all player moves, based on a provided screenshot and associated text.