modified readme

README.md

@@ -33,6 +33,9 @@ This is **not** a production model. It is a learning and research artifact.
 >
 > This decoder-only model was extracted from the original multimodal checkpoint using a custom extraction process. While it passes all internal stress tests (31/31), **it has not been evaluated on standardized medical benchmarks** (e.g., MedQA, PubMedQA, USMLE) and **has not undergone clinical validation**. Do not deploy this model in production healthcare systems, clinical decision support tools, or any patient-facing applications without extensive independent testing, medical expert review, and regulatory compliance evaluation. Use at your own risk.
 
+📦 **Model & weights:** [HuggingFace — vmanvs/medgemma-1.5-decoder-only-4b-it](https://huggingface.co/vmanvs/medgemma-1.5-decoder-only-4b-it)
+💻 **Extraction code & tests:** [GitHub — vmanvs/medgemma-1.5-decoder-only-4b-it](https://github.com/vmanvs/medgemma-1.5-decoder-only-4b-it)
+
 ---
 
 ## Model Details
@@ -98,7 +101,7 @@ This extraction exists for **research, education, and experimentation** — to a
 from transformers import AutoModelForCausalLM, AutoTokenizer
 import torch
 
-model_id = "your-username/medgemma-decoder-only-4b-it"  # Update with your HF repo
+model_id = "vmanvs/medgemma-1.5-decoder-only-4b-it"
 
 tokenizer = AutoTokenizer.from_pretrained(model_id)
 model = AutoModelForCausalLM.from_pretrained(