Update README.md

README.md

@@ -35,13 +35,32 @@ inference:
 
 # opt for email generation - 350M
 
-- This model is a fine-tuned version of [facebook/opt-350m](https://huggingface.co/facebook/opt-350m) on the [aeslc](https://huggingface.co/datasets/aeslc) dataset for six epochs. 
-- Emails, phone numbers, etc were attempted to be excluded in a dataset preparation step using [clean-text](https://pypi.org/project/clean-text/) in Python.
-- Note that API is restricted to generate 64 tokens - you can generate longer emails by using this in a text-generation `pipeline` object
+Why write the rest of your email when you can generate it?
+
+```
+from transformers import pipeline
+
+model_tag = "pszemraj/opt-350m-email-generation"
+generator = pipeline(
+              'text-generation', 
+              model=model_tag, 
+              do_sample=True,
+            )
+            
+prompt = """
+Hello, 
+I just wanted to follow up on the bubblegum shipment."""
+# generate
+generator(prompt)
+```
+
+> For this model, formatting matters. The results may be (significantly) different between the structure outlined above and `prompt = "Hey, just wanted to ..."` etc.
 
 ## Model description
 
-More information needed
+- This model is a fine-tuned version of [facebook/opt-350m](https://huggingface.co/facebook/opt-350m) on the [aeslc](https://huggingface.co/datasets/aeslc) dataset for six epochs. 
+- Emails, phone numbers, etc were attempted to be excluded in a dataset preparation step using [clean-text](https://pypi.org/project/clean-text/) in Python.
+- Note that API is restricted to generate 64 tokens - you can generate longer emails by using this in a text-generation `pipeline` object
 
 ## Intended uses & limitations