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  *Omni-Reasoner-2B* is based on Qwen2VL and is designed for mathematical and content-based explanations. It excels in providing detailed reasoning about content and solving math problems with proper content formatting. This model integrates a conversational approach with visual and textual understanding to handle multi-modal tasks effectively.
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- # Sample Inference with Doc**
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- ![omnip.png](https://cdn-uploads.huggingface.co/production/uploads/65bb837dbfb878f46c77de4c/53LkSMzAkIl1Yxc2yfLwb.png)
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  # **Use it with Transformers**
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  *Before using, ensure that the required libraries are successfully installed in the environment.*
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  *ChemQwen With Inference Documentation, **Before using, make sure that the `hf_token` is provided in the login field in the code below.***
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  ```python
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  # Authenticate with Hugging Face
 
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  *Omni-Reasoner-2B* is based on Qwen2VL and is designed for mathematical and content-based explanations. It excels in providing detailed reasoning about content and solving math problems with proper content formatting. This model integrates a conversational approach with visual and textual understanding to handle multi-modal tasks effectively.
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  # **Use it with Transformers**
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  *Before using, ensure that the required libraries are successfully installed in the environment.*
 
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  *ChemQwen With Inference Documentation, **Before using, make sure that the `hf_token` is provided in the login field in the code below.***
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+ # **Sample Inference with Doc**
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+ ![omnip.png](https://cdn-uploads.huggingface.co/production/uploads/65bb837dbfb878f46c77de4c/53LkSMzAkIl1Yxc2yfLwb.png)
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  ```python
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  # Authenticate with Hugging Face