Docs(Widget): Added 3 Bullet Examples

README.md

@@ -22,6 +22,13 @@ tags:
     - google
     - opera
     - justinthelaw
+widget:
+- text: "Using upwards of 3 sentences, expand upon the following Air and Space Force bullet statement by spelling-out acronyms and adding additional context that is not already included in the Air and Space Force bullet statement: - EFMP SME; dir'd 57 enrollments/194 incoming/101 outgoing inquiries--beat pkg processing time 50%/on-time rt 99%"
+  example_title: "Bullet Interpretation 1"
+- text: "Using upwards of 3 sentences, expand upon the following Air and Space Force bullet statement by spelling-out acronyms and adding additional context that is not already included in the Air and Space Force bullet statement: - Steered F22 DMS ops; led 9 mbrs/provided 24 hr MXS spt/returned 54 AFREP items--saved $258K/nailed 2K sorties"
+  example_title: "Bullet Interpretation 2"
+- text: "Using upwards of 3 sentences, expand upon the following Air and Space Force bullet statement by spelling-out acronyms and adding additional context that is not already included in the Air and Space Force bullet statement: - Setup Ex KEY RESOLVE '10 comms; installed 35 linesran 500ft cabling--supported multi-national operations"
+  example_title: "Bullet Interpretation 3"
 ---
 
 # Model Card for Opera Bullet Interpreter
@@ -43,7 +50,7 @@ To learn more about this project, please visit the [Opera GitHub Repository](htt
 - [Evaluation](#evaluation)
 - [Model Examination](#model-examination)
 - [Environmental Impact](#environmental-impact)
-- [Technical Specifications [optional]](#technical-specifications-optional)
+- [Technical Specifications](#technical-specifications-optional)
 - [Citation](#citation)
 - [Model Card Authors](#model-card-authors-optional)
 - [Model Card Contact](#model-card-contact)
@@ -72,7 +79,13 @@ This is a fine-tuned version of the LaMini-Flan-T5-783M, using the justinthelaw/
 
 Used to programmatically produce training data for Opera's Bullet Forge (see GitHub repository for details).
 
-## Downstream Use [Optional]
+The exact prompt to achieve the desired result is:
+
+```
+Using upwards of 3 sentences, expand upon the following Air and Space Force bullet statement by spelling-out acronyms and adding additional context that is not already included in the Air and Space Force bullet statement: <INSERT BULLET HERE>"
+```
+
+## Downstream Use
 
 Used to quickly interpret bullets written by Airman (Air Force) or Guardians (Space Force), into long-form, plain English sentences.
 
@@ -92,8 +105,6 @@ Look-up acronyms to ensure the correct narrative is being formed. Double-check (
 
 ## Training Data
 
-pre-processing or additional filtering. -->
-
 The model was fine-tuned on the justinthelaw/opera-bullet-completions dataset, which can be partially found at the GitHub repository.
 
 ## Training Procedure
@@ -170,8 +181,6 @@ VSCode, Jupyter Notebook, Python3, PyTorch, Transformers, Pandas, Asyncio, Logur
 
 # Model Card Authors
 
-construction? Etc. -->
-
 Justin Law, Alden Davidson, Christopher Kodama, My Tran
 
 # Model Card Contact
@@ -191,7 +200,8 @@ from transformers import T5ForConditionalGeneration, T5Tokenizer
 
 bullet_data_creation_prefix = (
     "Using upwards of 3 sentences, expand upon the following Air and Space Force bullet statement by "
-    + "spelling-out acronyms and adding additional context that is not already included in the Air and Space Force bullet statement: "
+    + "spelling-out acronyms and adding additional context that is not already included in the " +
+    "Air and Space Force bullet statement: "
 )
 
 # Path of the pre-trained model that will be used