diff --git a/docs/source/en/model_doc/llava_next.md b/docs/source/en/model_doc/llava_next.md
index ef74bf7e104ed5..a2a3913fcad7b8 100644
--- a/docs/source/en/model_doc/llava_next.md
+++ b/docs/source/en/model_doc/llava_next.md
@@ -98,7 +98,7 @@ print(processor.decode(output[0], skip_special_tokens=True))
 
 ### Quantization using Bitsandbytes
 
-The model can be loaded in 8 or 4 bits, greatly reducing the memory requirements while maintaining the performance of the original model. First make sure to install bitsandbytes, `pip install bitsandbytes`` and make sure to have access to a CUDA compatible GPU device. Simply change the snippet above with:
+The model can be loaded in 8 or 4 bits, greatly reducing the memory requirements while maintaining the performance of the original model. First make sure to install bitsandbytes, `pip install bitsandbytes` and make sure to have access to a CUDA compatible GPU device. Simply change the snippet above with:
 
 ```python
 from transformers import LlavaNextForConditionalGeneration, BitsAndBytesConfig
diff --git a/docs/source/en/model_doc/seggpt.md b/docs/source/en/model_doc/seggpt.md
index 707be240174629..f821fc14a08c54 100644
--- a/docs/source/en/model_doc/seggpt.md
+++ b/docs/source/en/model_doc/seggpt.md
@@ -36,7 +36,7 @@ import torch
 from datasets import load_dataset
 from transformers import SegGptImageProcessor, SegGptForImageSegmentation
 
-model_id = "BAAI/seggpt-vit-large"
+checkpoint = "BAAI/seggpt-vit-large"
 image_processor = SegGptImageProcessor.from_pretrained(checkpoint)
 model = SegGptForImageSegmentation.from_pretrained(checkpoint)
 
@@ -87,4 +87,4 @@ The original code can be found [here]([(https://github.com/baaivision/Painter/tr
 ## SegGptForImageSegmentation
 
 [[autodoc]] SegGptForImageSegmentation
-    - forward
\ No newline at end of file
+    - forward