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@@ -34,7 +34,7 @@ The model is trained on a dataset provided in CSV format (with a 'data' column)
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  - **Language(s) (NLP):** English
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  - **License:** Apache-2.0
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- ### Model Sources [optional]
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  - **Repository:** https://huggingface.co/aarohanverma/lstm-next-word-predictor
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  - **Demo:** [LSTM Next Word Predictor Demo](https://huggingface.co/spaces/aarohanverma/lstm-next-word-predictor-demo)
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  This model can be directly used for next word prediction in text autocompletion.
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- ### Downstream Use [optional]
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  <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
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  - Interpretability techniques such as examining predicted token distributions can be applied to further understand model behavior.
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- ## Technical Specifications [optional]
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  ### Model Architecture and Objective
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@@ -166,7 +166,16 @@ To run the model, follow these steps:
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  **BibTeX:**
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- [More Information Needed]
 
 
 
 
 
 
 
 
 
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  ## Model Card Contact
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  - **Language(s) (NLP):** English
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  - **License:** Apache-2.0
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+ ### Model Sources
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  - **Repository:** https://huggingface.co/aarohanverma/lstm-next-word-predictor
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  - **Demo:** [LSTM Next Word Predictor Demo](https://huggingface.co/spaces/aarohanverma/lstm-next-word-predictor-demo)
 
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  This model can be directly used for next word prediction in text autocompletion.
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+ ### Downstream Use
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  <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
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  - Interpretability techniques such as examining predicted token distributions can be applied to further understand model behavior.
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+ ## Technical Specifications
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  ### Model Architecture and Objective
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  **BibTeX:**
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+ ```bibtex
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+ @misc {aarohan_verma_2025,
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+ author = { {Aarohan Verma} },
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+ title = { lstm-next-word-predictor },
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+ year = 2025,
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+ url = { https://huggingface.co/aarohanverma/lstm-next-word-predictor },
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+ doi = { 10.57967/hf/4882 },
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+ publisher = { Hugging Face }
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+ }
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+ ```
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  ## Model Card Contact
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