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| tags: |
| - text-2-text-generation |
| - t5 |
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| --- |
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| # Model Card for EntityT5 |
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| # Model Details |
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| ## Model Description |
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| T5+Trie to predict entities of the last sentence in a dialogue. |
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| - **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 |
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| # Uses |
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| ## Direct Use |
| This model can be used for the task of text2text generation |
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| ## Downstream Use [Optional] |
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| More information needed. |
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| ## Out-of-Scope Use |
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| The model should not be used to intentionally create hostile or alienating environments for people. |
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| # Bias, Risks, and Limitations |
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| 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. |
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| ## Recommendations |
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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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| # Training Details |
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| ## Training Data |
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| More information needed |
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| ## Training Procedure |
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| ### Preprocessing |
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| More information needed |
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| ### Speeds, Sizes, Times |
| More information needed |
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| # Evaluation |
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| ## Testing Data, Factors & Metrics |
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| ### Testing Data |
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| More information needed |
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| ### Factors |
| More information needed |
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| ### Metrics |
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| More information needed |
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| ## Results |
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| More information needed |
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| # Model Examination |
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| More information needed |
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| # Environmental Impact |
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| 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). |
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| - **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 |
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| # Technical Specifications [optional] |
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| ## Model Architecture and Objective |
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| More information needed |
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| ## Compute Infrastructure |
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| More information needed |
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| ### Hardware |
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| More information needed |
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| ### Software |
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| More information needed. |
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| # Citation |
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| **BibTeX:** |
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| More information needed. |
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| # Glossary [optional] |
| More information needed |
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| # More Information [optional] |
| More information needed |
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| # Model Card Authors [optional] |
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| Jaren Yang in collaboration with Ezi Ozoani and the Hugging Face team |
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| # Model Card Contact |
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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. |
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| <details> |
| <summary> Click to expand </summary> |
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| ```python |
| from transformers import AutoTokenizer, AutoModelForSeq2SeqLM |
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| tokenizer = AutoTokenizer.from_pretrained("Jaren/EntityT5") |
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| model = AutoModelForSeq2SeqLM.from_pretrained("Jaren/EntityT5") |
| ``` |
| </details> |
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