Update README.md

README.md

@@ -11,11 +11,11 @@ tags:
   - small-model
 ---
 
-# DeepBrainz-R1-0.6B
+# DeepBrainz-R1-0.6B-Exp
 
-**DeepBrainz-R1-0.6B** is a compact, reasoning-focused language model designed for efficient problem-solving in **mathematics, logic, and code-related tasks**.
+**DeepBrainz-R1-0.6B-Exp** is a compact, reasoning-focused language model designed for efficient problem-solving in **mathematics, logic, and code-related tasks**.
 
-Despite its small size, R1-0.6B emphasizes **structured reasoning**, **stepwise problem decomposition**, and **stable generation behavior**, making it well-suited for research, education, and lightweight deployment scenarios.
+Despite its small size, R1-0.6B-Exp emphasizes experimental **structured reasoning**, **stepwise problem decomposition**, and **stable generation behavior**, making it well-suited for research, education, and lightweight deployment scenarios.
 
 ---
 
@@ -45,7 +45,7 @@ It is **not** intended as a general-purpose chat replacement for larger frontier
 ```python
 from transformers import AutoModelForCausalLM, AutoTokenizer
 
-model_id = "DeepBrainz/DeepBrainz-R1-0.6B"
+model_id = "DeepBrainz/DeepBrainz-R1-0.6B-Exp"
 
 tokenizer = AutoTokenizer.from_pretrained(model_id)
 model = AutoModelForCausalLM.from_pretrained(model_id)
@@ -68,7 +68,7 @@ print(tokenizer.decode(outputs[0], skip_special_tokens=True))
 
 ## Training & Alignment
 
-R1-0.6B was trained using modern post-training techniques emphasizing reasoning quality and generation stability.
+R1-0.6B-Exp was trained using modern post-training techniques emphasizing reasoning quality and generation stability.
 Specific training details are intentionally abstracted in this public-facing release.
 
 ---