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  ---
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  base_model: Qwen/Qwen2-VL-7B
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  library_name: peft
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- pipeline_tag: text-generation
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  tags:
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- - base_model:adapter:Qwen/Qwen2-VL-7B
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- - lora
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- - transformers
 
 
 
 
 
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  ---
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- # Model Card for Model ID
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  <!-- Provide a quick summary of what the model is/does. -->
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-
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-
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  ## Model Details
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- ### Model Description
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  <!-- Provide a longer summary of what this model is. -->
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- - **Developed by:** [More Information Needed]
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- - **Funded by [optional]:** [More Information Needed]
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- - **Shared by [optional]:** [More Information Needed]
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- - **Model type:** [More Information Needed]
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- - **Language(s) (NLP):** [More Information Needed]
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- - **License:** [More Information Needed]
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- - **Finetuned from model [optional]:** [More Information Needed]
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-
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  ### Model Sources [optional]
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  <!-- Provide the basic links for the model. -->
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  Use the code below to get started with the model.
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- [More Information Needed]
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  ## Training Details
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  ### Training Data
 
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  ---
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  base_model: Qwen/Qwen2-VL-7B
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  library_name: peft
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+ pipeline_tag: image-text-to-text
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  tags:
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+ - base_model:adapter:Qwen/Qwen2-VL-7B
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+ - lora
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+ - qwen2_vl
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+ - multimodal
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+ - transformers
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+ license: apache-2.0
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+ language:
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+ - en
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  ---
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+ # Model Card for MATRIX-PT
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  <!-- Provide a quick summary of what the model is/does. -->
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+ MATRIX-PT is a parameter-efficient LoRA adapter released by Radical AI for Qwen/Qwen2-VL-7B. It is designed to study post-training adaptations for materials science tasks, including theoretical reasoning, scientific problem solving, and multimodal reasoning over experimental images.
 
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  ## Model Details
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  <!-- Provide a longer summary of what this model is. -->
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+ ### Model Description
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+ - **Developed by:** Radical AI
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+ - **Model type:** LoRA adapter (PEFT) for a multimodal transformer (Qwen2-VL-7B)
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+ - **Base model:** `Qwen/Qwen2-VL-7B`
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+ - **Language(s):** English
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+ - **License:** mit
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+ - **Finetuned from model:** `Qwen/Qwen2-VL-7B`
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  ### Model Sources [optional]
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  <!-- Provide the basic links for the model. -->
 
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  Use the code below to get started with the model.
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+ ### Install
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+ ```bash
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+ pip install -U transformers peft accelerate torch
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+ ```
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  ## Training Details
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  ### Training Data