Model Card

README.md

@@ -8,11 +8,63 @@ datasets:
 - xsum
 thumbnail: https://huggingface.co/front/thumbnails/distilbart_medium.png
 ---
+# Distilbart-cnn-12-6
 
-### Usage
+## Table of Contents
+- [Model Details](#model-details)
+- [How to Get Started With the Model](#how-to-get-started-with-the-model)
+- [Uses](#uses)
+- [Risks, Limitations and Biases](#risks-limitations-and-biases)
+- [Training](#training)
+- [Evaluation](#evaluation)
+
+## Model Details
+- **Model Description:**
+- **Developed by:** Sam Shleifer
+- **Model Type:** Summarization
+- **Language(s):** English
+- **License:** Apache-2.0
+- **Parent Model:** See the [BART large CNN model](https://huggingface.co/facebook/bart-large-cnn) for more information about the BART large-sized model which is similarly trained on [CNN Dailymail](https://huggingface.co/datasets/cnn_dailymail) dataset.
+- **Resources for more information:**
+  - [Bart Document](https://huggingface.co/docs/transformers/model_doc/bart#transformers.BartForConditionalGeneration)
+  - [BART large CNN model paper](https://arxiv.org/abs/1910.13461)
+
+
+## How to Get Started With the Model
+```python
+​​from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
+
+tokenizer = AutoTokenizer.from_pretrained("sshleifer/distilbart-cnn-12-6")
+
+model = AutoModelForSeq2SeqLM.from_pretrained("sshleifer/distilbart-cnn-12-6")
+
+```
+
+
+## Uses
+
+
+#### Direct Use
+This model can be used for text summerzation.
+
+
+## Risks, Limitations and Biases
+### Limitations
+This model makes use of the [CNN Dailymail](https://huggingface.co/datasets/cnn_dailymail) dataset, which is an English-language dataset containing just over 300k unique news articles as written by journalists at CNN and the Daily Mail.
+The BCP-47 code for English as generally spoken in the United States is en-US and the BCP-47 code for English as generally spoken in the United Kingdom is en-GB. It is unknown if other varieties of English are represented in the data.
+
+### Biases
+[Bordia and Bowman (2019)](https://www.aclweb.org/anthology/N19-3002.pdf) explore measuring gender bias and debiasing techniques in the CNN / Dailymail dataset, the Penn Treebank, and WikiText-2. They find the CNN / Dailymail dataset to have a slightly lower gender bias based on their metric compared to the other datasets, but still show evidence of gender bias when looking at words such as 'fragile'.
+
+Further information e.g in regards to uses, out-of-scope uses, training procedure for the CNN Dailymail dataset are available within its [dataset card](https://huggingface.co/datasets/cnn_dailymail).
+
+
+## Training
 
 This checkpoint should be loaded into `BartForConditionalGeneration.from_pretrained`. See the [BART docs](https://huggingface.co/transformers/model_doc/bart.html?#transformers.BartForConditionalGeneration) for more information.
 
+## Evaluation 
+
 ### Metrics for DistilBART models
 
 | Model Name                 |   MM Params |   Inference Time (MS) |   Speedup |   Rouge 2 |   Rouge-L |