Update README.md

README.md

@@ -56,6 +56,35 @@ output = model.generate(**inputs, max_new_tokens=100)
 
 print(processor.decode(output[0], skip_special_tokens=True))
 ```
+
+### Model optimization
+
+#### 4-bit quantization through `bitsandbytes` library
+
+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: 
+
+```diff
+model = LlavaNextForConditionalGeneration.from_pretrained(
+    model_id, 
+    torch_dtype=torch.float16, 
+    low_cpu_mem_usage=True,
++   load_in_4bit=True
+)
+```
+
+#### Use Flash-Attention 2 to further speed-up generation
+
+First make sure to install `flash-attn`. Refer to the [original repository of Flash Attention](https://github.com/Dao-AILab/flash-attention) regarding that package installation. Simply change the snippet above with: 
+
+```diff
+model = LlavaNextForConditionalGeneration.from_pretrained(
+    model_id, 
+    torch_dtype=torch.float16, 
+    low_cpu_mem_usage=True,
++   use_flash_attention_2=True
+).to(0)
+```
+
 ### BibTeX entry and citation info
 
 ```bibtex