model documentation

README.md

@@ -0,0 +1,184 @@
+---
+tags:
+- text-2-text-generation
+- t5
+---
+
+# Model Card for t5_sentence_paraphraser
+ 
+# Model Details
+ 
+## Model Description
+ 
+
+Using this model you can generate paraphrases of any given question.
+
+
+ 
+- **Developed by:** Ramsri Goutham Golla
+- **Shared by [Optional]:** Ramsri Goutham Golla
+- **Model type:** Text2Text Generation
+- **Language(s) (NLP):** More information needed
+- **License:** More information needed
+- **Parent Model:** [All T5 Checkpoints](https://huggingface.co/models?search=t5)
+- **Resources for more information:** 
+    - [GitHub Repo](https://github.com/ramsrigouthamg/Paraphrase-any-question-with-T5-Text-To-Text-Transfer-Transformer-)
+   - [Blog Post](https://towardsdatascience.com/paraphrase-any-question-with-t5-text-to-text-transfer-transformer-pretrained-model-and-cbb9e35f1555)
+# 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
+ 
+The developers also write in a [blog post](https://towardsdatascience.com/paraphrase-any-question-with-t5-text-to-text-transfer-transformer-pretrained-model-and-cbb9e35f1555) that the model: 
+ 
+>  [Quora Question Pairs](https://www.quora.com/q/quoradata/First-Quora-Dataset-Release-Question-Pairs) dataset to collect all the questions marked as **duplicates** and prepared training and validation sets. Questions that are duplicates serve our purpose of getting **paraphrase** pairs.
+ 
+ 
+ 
+## Training Procedure
+
+The developers also write in a [blog post](https://towardsdatascience.com/paraphrase-any-question-with-t5-text-to-text-transfer-transformer-pretrained-model-and-cbb9e35f1555) that the model: 
+ 
+> I trained T5 with the **original sentence** as **input** and **paraphrased** (duplicate sentence from Quora Question pairs) sentence as **output**.
+ 
+### 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:** p2.xlarge
+- **Hours used:** ~20 hrs
+- **Cloud Provider:** AWS ec2
+- **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
+
+
+
+
+
+**APA:**
+
+More information needed
+  
+# Glossary [optional]
+ 
+More information needed
+
+# More Information [optional]
+More information needed 
+
+# Model Card Authors [optional]
+ 
+Ramsri Goutham Golla  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("ramsrigouthamg/t5_sentence_paraphraser")
+
+model = AutoModelForSeq2SeqLM.from_pretrained("ramsrigouthamg/t5_sentence_paraphraser")
+ ```
+
+See the [blog post](https://towardsdatascience.com/paraphrase-any-question-with-t5-text-to-text-transfer-transformer-pretrained-model-and-cbb9e35f1555) and this [Colab Notebook](https://colab.research.google.com/drive/176NSaYjc2eeI-78oLH_F9-YV3po3qQQO?usp=sharing#scrollTo=SDVQ04fGRb1v) for more examples.
+</details>
+
+