Update README.md

README.md

@@ -1,5 +1,5 @@
 ---
-title: 'Summ Small: Medical Dialogue to SOAP Summarizer'
+title: 'Sum Small: Medical Dialogue to SOAP Summarizer'
 emoji: 📄
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 colorTo: pink
@@ -14,11 +14,11 @@ metrics:
 - rouge
 ---
 
-# Model Card for Summ (3B) Small
+# Model Card for Sum (3B) Small
 
 ## Model Description
 
-Summ Small is a powerful language model specifically designed to generate SOAP summaries from medical dialogues. It is a fine-tuned version of the [Microsoft/Phi-3-mini-4k-instruct](https://huggingface.co/microsoft/Phi-3-mini-4k-instruct) using the [Omi Health/medical-dialogue-to-soap-summary dataset](https://huggingface.co/datasets/omi-health/medical-dialogue-to-soap-summary). This model demonstrates superior performance compared to larger models like GPT-4.
+Sum Small is a powerful language model specifically designed to generate SOAP summaries from medical dialogues. It is a fine-tuned version of the [Microsoft/Phi-3-mini-4k-instruct](https://huggingface.co/microsoft/Phi-3-mini-4k-instruct) using the [Omi Health/medical-dialogue-to-soap-summary dataset](https://huggingface.co/datasets/omi-health/medical-dialogue-to-soap-summary). This model demonstrates superior performance compared to larger models like GPT-4.
 
 ## Intended Use
 
@@ -45,15 +45,15 @@ The performance of Summ Small has been evaluated using several Rouge metrics as
 | Phi-3 3B mini 4k instruct| 55      | 32      | 40      | 50         |
 | Phi2 basic               | 41      | 19      | 26      | 36         |
 
-These results showcase Summ Small's capabilities in generating accurate SOAP summaries compared to other leading models.
+These results showcase Sum Small's capabilities in generating accurate SOAP summaries compared to other leading models.
 
 ## Limitations
 
-While Summ Small demonstrates promising results, the training data is completely synthetic and not derived from actual clinical interactions. Care must be taken when considering this model for practical applications, as it requires significant testing and adaptation to meet clinical safety standards.
+While Sum Small demonstrates promising results, the training data is completely synthetic and not derived from actual clinical interactions. Care must be taken when considering this model for practical applications, as it requires significant testing and adaptation to meet clinical safety standards.
 
 ## Licensing
 
-The Summ Small model is released under the MIT License, which permits broad use with fewer restrictions, making it accessible for both commercial and non-commercial use.
+The Sum Small model is released under the MIT License, which permits broad use with fewer restrictions, making it accessible for both commercial and non-commercial use.
 
 ## Ethical Considerations
 
@@ -61,4 +61,4 @@ Users are urged to consider the ethical implications of AI in healthcare and ens
 
 ## Contact
 
-For more information or to request access to Summ Small, please contact [info@omi.health](mailto:info@omi.health).
+For more information or to request access to Sum Small API, please contact [info@omi.health](mailto:info@omi.health).