Update README.md

README.md

@@ -8,14 +8,18 @@ base_model:
 
 ## Model Information
 
-The Goodfire SAE (Sparse Autoencoder) for Llama 3.3 70B is an interpreter model designed to analyze and understand 
-the internal representations of Llama-3.3-70B-Instruct. This SAE model is trained specifically on layer 50 of 
+The Goodfire SAE (Sparse Autoencoder) for [meta-llama/Llama-3.3-70B-Instruct](https://huggingface.co/meta-llama/Llama-3.3-70B-Instruct) 
+is an interpreter model designed to analyze and understand 
+the model's internal representations. This SAE model is trained specifically on layer 50 of 
 Llama 3.3 70B and achieves an L0 count of 121, enabling the decomposition of complex neural activations 
 into interpretable features. The model is optimized for interpretability tasks and model steering applications, 
 allowing researchers and developers to gain insights into the model's internal processing and behavior patterns. 
 As an open-source tool, it serves as a foundation for advancing interpretability research and enhancing control 
 over large language model operations.
 
+__Model Creator__: [meta-llama](https://huggingface.co/meta-llama)
+
+
 ## Intended Use
 
 By open-sourcing SAEs for leading open models, especially large-scale 
@@ -272,8 +276,6 @@ logits, kv_cache, features = llama_3_1_8b.forward(
 print(llama_3_1_8b.tokenizer.decode(logits[-1].argmax(-1)))
 ```
 
-## Training
-
 ## Responsibility & Safety
 
 Safety is at the core of everything we do at Goodfire. As a public benefit