Update models.py

models.py

@@ -112,7 +112,7 @@ class OpenAIModel(BaseTCOModel):
         
         self.labor = gr.Number(0, visible=False, 
                                 label="($) Labor cost per month", 
-                                info="This is how much it will cost you to have an engineer specialized in Machine Learning take care of the deployment of your model service",
+                                info="This is an estimate of the labor cost of the AI engineer in charge of deploying the model",
                                 interactive=True
                                 )
 
@@ -144,8 +144,9 @@ class OpenSourceLlama2Model(BaseTCOModel):
                               visible=False,
                               label="Instance of VM with GPU",
                               )
-        self.vm_cost_per_hour = gr.Number(2.21, label="VM instance cost ($) per hour", info="Note that this is the cost for a single VM instance, it is doubled in our case since two GPUs are needed",
+        self.vm_cost_per_hour = gr.Number(4.42, label="Instance cost ($) per hour",
                                       interactive=False, visible=False)
+        self.info_vm = gr.Markdown("This price above is from [CoreWeave's pricing web page](https://www.coreweave.com/gpu-cloud-pricing)", interactive=False, visible=False)
         self.input_tokens_cost_per_second = gr.Number(0.00052, visible=False,
                                            label="($) Price/1K input prompt tokens",
                                            interactive=False
@@ -154,18 +155,17 @@ class OpenSourceLlama2Model(BaseTCOModel):
                                            label="($) Price/1K output prompt tokens",
                                            interactive=False
                                            )
-        self.info = gr.Markdown("For the Llama2-70B model, we took the cost per input and output tokens values from [these benchmark results](https://www.cursor.so/blog/llama-inference#user-content-fn-llama-paper)", interactive=False, visible=False)
+        self.source = gr.Markdown("""<span style="font-size: 16px; font-weight: 600; color: #212529;">Source</span>""")
+        self.info = gr.Markdown("The cost per input and output tokens values above are from [these benchmark results](https://www.cursor.so/blog/llama-inference#user-content-fn-llama-paper)", 
+                                 label="Source", 
+                                 interactive=False, 
+                                 visible=False)
         
         self.labor = gr.Number(10000, visible=False, 
                                 label="($) Labor cost per month",
-                                info="This is how much it will cost you to have an engineer specialized in Machine Learning take care of the deployment of your model service",
+                                info="This is an estimate of the labor cost of the AI engineer in charge of deploying the model",
                                 interactive=True
                                 )
-        
-        # self.used = gr.Slider(minimum=0.01, value=30., step=0.01, label="% used", 
-        #                            info="Percentage of time the GPU is used",
-        #                            interactive=True,
-        #                            visible=False)
 
     def compute_cost_per_token(self, input_tokens_cost_per_second, output_tokens_cost_per_second, labor):
         cost_per_input_token = (input_tokens_cost_per_second / 1000) 
@@ -201,7 +201,7 @@ class CohereModel(BaseTCOModel):
 
         self.labor = gr.Number(0, visible=False, 
                                 label="($) Labor cost per month", 
-                                info="This is how much it will cost you to have an engineer specialized in Machine Learning take care of the deployment of your model service",
+                                info="This is an estimate of the labor cost of the AI engineer in charge of deploying the model",
                                 interactive=True
                                 )
 
@@ -254,7 +254,7 @@ class ModelPage:
         for model in self.models:
             if model.get_name() == name:
                 output+= [gr.update(visible=True)] * len(model.get_components()) 
-                # Set use_case and num_users values in the model
+                # Set use_case value in the model
                 model.use_case = use_case
             else:
                 output+= [gr.update(visible=False)] * len(model.get_components())