readme: ---
  tags:
  - text-2-text-generation
  - t5
  
  ---
  
  # Model Card for EntityT5
   
  # Model Details
   
  ## Model Description
   
  T5+Trie to predict entities of the last sentence in a dialogue.
   
  - **Developed by:** Jaren Yang
  - **Shared by [Optional]:** Jaren Yang
  - **Model type:** Text2text Generation 
  - **Language(s) (NLP):** More information needed
  - **License:** More information needed 
  - **Parent Model:** T5
  - **Resources for more information:** More information needed 
   	
  
  
  # Uses
   
  
  ## Direct Use
  This model can be used for the task of text2text generation 
   
  ## Downstream Use [Optional]
   
  More information needed.
   
  ## Out-of-Scope Use
   
  The model should not be used to intentionally create hostile or alienating environments for people. 
   
  # Bias, Risks, and Limitations
   
   
  Significant research has explored bias and fairness issues with language models (see, e.g., [Sheng et al. (2021)](https://aclanthology.org/2021.acl-long.330.pdf) and [Bender et al. (2021)](https://dl.acm.org/doi/pdf/10.1145/3442188.3445922)). Predictions generated by the model may include disturbing and harmful stereotypes across protected classes; identity characteristics; and sensitive, social, and occupational groups.
  
  
  
  ## Recommendations
   
   
  Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
  
  # Training Details
   
  ## Training Data
   
  More information needed 
   
  ## Training Procedure
  
   
  ### Preprocessing
   
  More information needed 
   
  ### Speeds, Sizes, Times
  More information needed 
  
   
  # Evaluation
   
   
  ## Testing Data, Factors & Metrics
   
  ### Testing Data
   
  More information needed 
   
   
  ### Factors
  More information needed
   
  ### Metrics
   
  More information needed
   
   
  ## Results 
   
  More information needed
  
   
  # Model Examination
   
  More information needed
   
  # Environmental Impact
   
  Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
   
  - **Hardware Type:** More information needed
  - **Hours used:** More information needed
  - **Cloud Provider:** More information needed
  - **Compute Region:** More information needed
  - **Carbon Emitted:** More information needed
   
  # Technical Specifications [optional]
   
  ## Model Architecture and Objective
  
  More information needed 
   
  ## Compute Infrastructure
   
  More information needed 
   
  ### Hardware
   
   
  More information needed
   
  ### Software
   
  More information needed.
   
  # Citation
  
   
  **BibTeX:**
  
  More information needed.
   
   
   
   
  # Glossary [optional]
  More information needed 
   
  # More Information [optional]
  More information needed 
  
   
  # Model Card Authors [optional]
   
  Jaren Yang in collaboration with Ezi Ozoani and the Hugging Face team
  
  
  # Model Card Contact
   
  More information needed
   
  # How to Get Started with the Model
   
  Use the code below to get started with the model.
   
  <details>
  <summary> Click to expand </summary>
  
  ```python
  from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
  
  tokenizer = AutoTokenizer.from_pretrained("Jaren/EntityT5")
  
  model = AutoModelForSeq2SeqLM.from_pretrained("Jaren/EntityT5")
   ```
  </details>
  