v3

app.py

@@ -5,7 +5,6 @@ import io
 from typing import Any, Tuple
 import os
 
-
 class Client:
     def __init__(self, server_url: str):
         self.server_url = server_url
@@ -40,7 +39,8 @@ with gr.Blocks() as demo:
         model_selector = gr.Dropdown(
             choices=[
                 "facebook/opt-1.3b",
-                "facebook/opt-2.7b",
+                "TheBloke/Llama-2-7B-fp16"
+                # "facebook/opt-2.7b",
                 # "microsoft/Phi-3-mini-128k-instruct"
             ],
             value="facebook/opt-1.3b",
@@ -50,8 +50,8 @@ with gr.Blocks() as demo:
             choices=[
                 "Layer wise non-linearity (with first layer)", 
                 "Next-token prediction from intermediate representations", 
-                "Contextualization mesurment",
-                "Layerwise predictions and losses",
+                "Contextualization measurement",
+                "Layerwise predictions (logit lens)",
                 "Tokenwise loss without i-th layer"
             ], 
             value="Layer wise non-linearity (with first layer)",
@@ -78,15 +78,15 @@ with gr.Blocks() as demo:
                 return "token-wise"
             if task_name == "Next-token prediction from intermediate representations":
                 return "token-wise"
-            if task_name == "Contextualization mesurment":
+            if task_name == "Contextualization measurement":
                 return "global"
-            if task_name == "Layerwise predictions and losses":
+            if task_name == "Layerwise predictions (logit lens)":
                 return "global"
             if task_name == "Tokenwise loss without i-th layer":
                 return "token-wise"
 
         def check_normalization(task_name: str, normalization_name) -> Tuple[str, str]:
-            if task_name == "Contextualization mesurment" and normalization_name == "token-wise":
+            if task_name == "Contextualization measurement" and normalization_name == "token-wise":
                 return ("global", "\nALERT: Cannot apply token-wise normalization to one sentence, setting global normalization\n")
             return (normalization_name, "")