Update README.md

README.md

@@ -2,10 +2,6 @@
 license: mit
 datasets:
 - ncbi/pubmed
-- starmpcc/Asclepius-Synthetic-Clinical-Notes
-- akemiH/NoteChat
-- zhengyun21/PMC-Patients
-- jpcorb20/medical_wikipedia
 language:
 - en
 base_model:
@@ -26,7 +22,7 @@ The MediPhi Model Collection comprises 7 small language models of 3.8B parameter
 ## Model Details
 ### Model Description
 
-This model is `MediPhi` obtained by merging all 5 experts with the BreadCrumbs technique into this unified expert.
+This model is `MediPhi-PubMed` obtained by merging the fine-tuned PubMed expert with the SLERP technique into the base model at 10%.
 
 - **Developed by:** Microsoft Healthcare \& Life Sciences
 - **Model type:** Phi3
@@ -90,7 +86,7 @@ Researchers should apply responsible AI best practices, including mapping, measu
 
     torch.random.manual_seed(0)
 
-    model_name = "microsoft/MediPhi"
+    model_name = "microsoft/MediPhi-PubMed"
     model = AutoModelForCausalLM.from_pretrained(
         model_name,
         device_map="cuda",
@@ -135,12 +131,6 @@ Check `microsoft/Phi-3.5-mini-instruct` for details about the tokenizer, require
 
 Continual Pre-training:
 - PubMed (commercial subset) and abstracts from `ncbi/pubmed`.
-- Medical Guideline `epfl-llm/guidelines`.
-- Medical Wikipedia `jpcorb20/medical_wikipedia`.
-- Medical Coding: ICD10CM, ICD10PROC, ICD9CM, ICD9PROC, and ATC.
-- Clinical documents:
-    - `zhengyun21/PMC-Patients`, `akemiH/NoteChat`, and `starmpcc/Asclepius-Synthetic-Clinical-Notes` (only commercial-friendly licenses across all three datasets)
-    - mtsamples
 
 See paper for details.