diff --git a/README.md b/README.md
index 2da63eb..e6a460a 100644
--- a/README.md
+++ b/README.md
@@ -108,11 +108,14 @@ cmake --build build -j$(nproc)
 ```bash
 # Pre-tokenize your prompt (diffuse-cpp does not include a tokenizer)
 # Use transformers or tiktoken to get token IDs as a comma-separated list
+# CRITICAL: Use the correct tokenizer for your model.
+#   LLaDA → GSAI-ML/LLaDA-8B-Instruct
+#   Dream → Dream-org/Dream-v0-Instruct-7B
 
-# Generate text (example with token IDs)
+# Generate text (example for LLaDA with "What is the capital of France?")
 ./build/diffuse-cli \
     -m model.gguf \
-    --tokens "128000,3923,374,279,6864,315,9822,30" \
+    --tokens "2372,341,268,7706,300,11406,30" \
     -n 256 \
     -s 16 \
     -t 12 \
@@ -123,7 +126,7 @@ cmake --build build -j$(nproc)
 
 ```python
 from transformers import AutoTokenizer
-tokenizer = AutoTokenizer.from_pretrained("LLaDA-8B-Instruct")
+tokenizer = AutoTokenizer.from_pretrained("GSAI-ML/LLaDA-8B-Instruct", trust_remote_code=True)
 tokens = tokenizer.encode("What is the capital of France?")
 print(",".join(map(str, tokens)))
 ```
@@ -272,7 +275,7 @@ params.remasking = diffuse_remasking::ENTROPY_EXIT;
 params.entropy_threshold = 1.5f;
 
 // Generate
-std::vector<int32_t> prompt_tokens = {128000, 3923, 374};
+std::vector<int32_t> prompt_tokens = {2372, 341, 268, 7706, 300, 11406, 30};
 auto output = diffuse_generate(ctx, prompt_tokens, 256, params);
 
 // Cleanup