Update app.py

app.py

@@ -39,16 +39,16 @@ def generate(
     ctx,
     image_features,
     token_count=200,
-    temperature=0.2,
+    temperature=1.0,
     top_p=0.3,
     presencePenalty = 0.1,
     countPenalty = 0.1,
 ):
     args = PIPELINE_ARGS(temperature = max(0.2, float(temperature)), top_p = float(top_p),
-                     alpha_frequency = countPenalty,
-                     alpha_presence = presencePenalty,
-                     token_ban = [], # ban the generation of some tokens
-                     token_stop = [0, 261]) # stop generation whenever you see any token here
+                    alpha_frequency = countPenalty,
+                    alpha_presence = presencePenalty,
+                    token_ban = [], # ban the generation of some tokens
+                    token_stop = [0, 261]) # stop generation whenever you see any token here
     ctx = ctx.strip()
     all_tokens = []
     out_last = 0
@@ -56,9 +56,11 @@ def generate(
     occurrence = {}
     for i in range(int(token_count)):
         if i == 0:
+            prefix_ids = pipeline.encode("User: ")
+            prefix_embs = model.w['emb.weight'][prefix_ids]
             input_ids = pipeline.encode(ctx)
             text_embs = model.w['emb.weight'][input_ids]
-            input_embs = torch.cat((image_features, text_embs), dim=0)[-ctx_limit:]
+            input_embs = torch.cat((prefix_embs, image_features, text_embs), dim=0)[-ctx_limit:]
             out, state = model.forward(embs=input_embs, state=None)
         else:
             input_ids = [token]