diff --git a/README.md b/README.md
index 03850f4..4350968 100644
--- a/README.md
+++ b/README.md
@@ -88,7 +88,7 @@ The below example should run on a RTX 4090. For more examples check the [diffuse
 
 ```python
 import torch
-from diffusers import Flux2Pipeline, Flux2Transformer2DModel
+from diffusers import Flux2Pipeline
 from diffusers.utils import load_image
 from huggingface_hub import get_token
 import requests
@@ -112,7 +112,7 @@ def remote_text_encoder(prompts):
     return prompt_embeds.to(device)
 
 pipe = Flux2Pipeline.from_pretrained(
-    repo_id, transformer=transformer, text_encoder=None, torch_dtype=torch_dtype
+    repo_id, text_encoder=None, torch_dtype=torch_dtype
 ).to(device)
 
 prompt = "Realistic macro photograph of a hermit crab using a soda can as its shell, partially emerging from the can, captured with sharp detail and natural colors, on a sunlit beach with soft shadows and a shallow depth of field, with blurred ocean waves in the background. The can has the text `BFL Diffusers` on it and it has a color gradient that start with #FF5733 at the top and transitions to #33FF57 at the bottom."
diff --git a/docs/flux2_dev_hf.md b/docs/flux2_dev_hf.md
index acee3da..9c057c9 100644
--- a/docs/flux2_dev_hf.md
+++ b/docs/flux2_dev_hf.md
@@ -77,15 +77,22 @@ The text-encoder is offloaded from VRAM for the transformer to run with `pipe.en
 
 ```py
 import torch
-from diffusers import Flux2Pipeline
+from diffusers import Flux2Pipeline, AutoModel
+from transformers import Mistral3ForConditionalGeneration
 from diffusers.utils import load_image
 
 repo_id = "diffusers/FLUX.2-dev-bnb-4bit" #quantized text-encoder and DiT. VAE still in bf16
 device = "cuda:0"
 torch_dtype = torch.bfloat16
 
+text_encoder = Mistral3ForConditionalGeneration.from_pretrained(
+    repo_id, subfolder="text_encoder", torch_dtype=torch.bfloat16, device_map="cpu"
+)
+dit = AutoModel.from_pretrained(
+    repo_id, subfolder="transformer", torch_dtype=torch.bfloat16, device_map="cpu"
+)
 pipe = Flux2Pipeline.from_pretrained(
-    repo_id, torch_dtype=torch_dtype
+    repo_id, text_encoder=text_encoder, transformer=dit, torch_dtype=torch_dtype
 )
 pipe.enable_model_cpu_offload()