Upload README.md

README.md

@@ -1,14 +1,15 @@
 ---
-language: en
-license: mit
+language:
+  language: en
+  license: mit
 ---
 
 # model-card-testing
 
-model-card-testing is a distilled language model that can be used for text generation. Users of this model card should also consider information about the design, training, and limitations of gpt2.
-
 ## Model Details
 
+model-card-testing is a distilled language model. Users of this model card should also consider information about the design, training, and limitations of gpt2.
+
 - **Developed by:** author1, author2
 - **Model type:** testing type
 - **Language(s):**  # not working right now
@@ -18,17 +19,10 @@ model-card-testing is a distilled language model that can be used for text gener
     - **Parent Model**: gpt2
     - **Sibling Models**: TO DO (could we do this automatically somehow?)
 
-## How to Get Started with the Model 
 
-Use the code below to get started with the model.  model-card-testing can be used directly with a pipeline for text generation. 
-Since the generation relies on some randomness, we set a seed for reproducibility:
-```python
->>> from transformers import pipeline, set_seed
->>> generator = pipeline('text-generation', model='model-card-testing')
->>> set_seed(42)
->>> generator("Hello, I'm a language model," max_length=20, num_return_sequences=5)
-```
+## How to Get Started with the Model 
 
+Use the code below to get started with the model. 
 
 
 
@@ -95,16 +89,6 @@ The impact of model compression techniques, such as knowledge distillation, on b
 NOTE: This code will need customization/fixing.
 
 
-```python
->>> from transformers import pipeline, set_seed
->>> generator = pipeline('text-generation', model='model-card-testing')
->>> set_seed(48)
->>> generator("The White man worked as a", max_length=20, num_return_sequences=3)
-
->>> set_seed(48)
->>> generator("The Black man worked as a", max_length=20, num_return_sequences=3)
-```
-
 
 
 
@@ -123,11 +107,6 @@ This model achieves the following results:
 NOTE: This will need customization.
 
 
-| Dataset  | LAMBADA | LAMBADA | CBT-CN | CBT-NE | WikiText2 | PTB    | enwiki8 | text8  | WikiText103 | 1BW   |
-|:--------:|:-------:|:-------:|:------:|:------:|:---------:|:------:|:-------:|:------:|:-----------:|:-----:|
-| (metric) | (PPL)   | (ACC)   | (ACC)  | (ACC)  | (PPL)     | (PPL)  | (BPB)   | (BPC)  | (PPL)       | (PPL) |
-|          |         |         |        |        |           |        |         |        |             |       |
-
 
 
 
@@ -141,9 +120,7 @@ You can estimate carbon emissions using the [Machine Learning Impact calculator]
 - **Compute Region:** 
 - **Carbon Emitted** *(Power consumption x Time x Carbon produced based on location of power grid)*:
 
-## Add interpretability section?
-
-### BibTeX Entry and Citation Info
+### Citation Information
 
 ```bibtex
 @inproceedings{...,