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  library_name: transformers
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- tags: []
 
 
 
 
 
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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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  ## 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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- This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.
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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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  ### Model Sources [optional]
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- <!-- Provide the basic links for the model. -->
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- - **Repository:** [More Information Needed]
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- - **Paper [optional]:** [More Information Needed]
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- - **Demo [optional]:** [More Information Needed]
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  ## Uses
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- <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
 
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  ### Direct Use
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- <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
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- [More Information Needed]
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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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- [More Information Needed]
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- ### Out-of-Scope Use
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- <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
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- [More Information Needed]
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  ## Bias, Risks, and Limitations
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- <!-- This section is meant to convey both technical and sociotechnical limitations. -->
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  [More Information Needed]
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- ### Recommendations
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- <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
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- Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
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  ## How to Get Started with the Model
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  Use the code below to get started with the model.
 
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  library_name: transformers
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+ license: mit
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+ language:
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+ - en
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+ base_model:
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+ - google-bert/bert-base-uncased
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+ pipeline_tag: text-classification
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  ---
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  # Model Card for Model ID
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+ Texts text input and classifies the text into 8 classes of emotions- neutral, anger, love, fear, hate, happiness, sadness, surprise
 
 
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  ## Model Details
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  ### Model Description
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+ - **Developed by:** Antareep, Eswar, Subhasish
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+ - **Model type:** Large Language Model(LLM)
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+ - **Language(s) (NLP):** English
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+ - **License:** MIT
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+ - **Finetuned from model:** BERT-Base
 
 
 
 
 
 
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  ### Model Sources [optional]
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+ - **Repository:** https://huggingface.co/google-bert/bert-base-uncased
 
 
 
 
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  ## Uses
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+ - Fine-tune further on more data
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+ - Emotion classification tasks
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  ### Direct Use
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+ Check out this app- https://huggingface.co/spaces/user-anto/text-emotion-classifier
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ## Bias, Risks, and Limitations
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+ - This model gets confused with text input corresponding to the emotion 'angry'.
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  [More Information Needed]
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  ## How to Get Started with the Model
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  Use the code below to get started with the model.