Update README.md

README.md

@@ -20,8 +20,6 @@ tags:
 datasets:
 - lamm-mit/Cephalo-Bioinspired-Mechanics-Materials
 - lamm-mit/Cephalo-Wikipedia-Materials
-- OleehyO/latex-formulas
-- lamm-mit/OleehyO-latex-formulas
 pipeline_tag: image-text-to-text
 inference:
   parameters:
@@ -146,7 +144,11 @@ for file_name in tqdm(py_files):
 print("Download completed.")
 ```
 
-Download models that will form the experts, as well as the base model:
+Download models that will form the experts, as well as the base model. As a simple example, we use 
+
+1) Materials-science fine-tuned model: lamm-mit/Cephalo-Idefics-2-vision-8b-beta (model_1)
+2) A chatty version: HuggingFaceM4/idefics2-8b-chatty (model_1) (model_2)
+3) A basic variant: HuggingFaceM4/idefics2-8b (model_3)
 
 ```python
 from transformers import AutoProcessor, Idefics2ForConditionalGeneration , AutoTokenizer
@@ -168,7 +170,7 @@ model_1 = Idefics2ForConditionalGeneration.from_pretrained(  model_id_1,
                                                            _attn_implementation="flash_attention_2", #make sure Flash Attention 2 is installed
                                                            trust_remote_code=True,
                                                            #quantization_config=quantization_config,
-                                                        ) 
+                                                          ) 
 processor = AutoProcessor.from_pretrained(
     f"{model_id_1}",
     do_image_splitting=True
@@ -189,7 +191,7 @@ model_2 = Idefics2ForConditionalGeneration.from_pretrained(  model_id_2,
                                                            _attn_implementation="flash_attention_2", #make sure Flash Attention 2 is installed
                                                            trust_remote_code=True,
                                                            #quantization_config=quantization_config,
-                                                        ) 
+                                                          ) 
 
 model_id_3='HuggingFaceM4/idefics2-8b'
 
@@ -198,7 +200,7 @@ model_3 = Idefics2ForConditionalGeneration.from_pretrained(  model_id_3,
                                                            _attn_implementation="flash_attention_2", #make sure Flash Attention 2 is installed
                                                            trust_remote_code=True,
                                                            #quantization_config=quantization_config,
-                                                        ) 
+                                                          ) 
 ```
 Put on device:
 ```python