Actually works properly

prior versions were generated using CLIPModel.
Turns out thats the WRONG model. Now using the same code that SD actually uses: CLIPTextModel

generate-embedding.py

@@ -3,7 +3,6 @@
 """ Work in progress
 NB: This is COMPLETELY DIFFERENT from "generate-embeddings.py"!!!
 
-
 Plan:
    Take input for a single word or phrase.
    Generate a embedding file, "generated.safetensors"
@@ -20,7 +19,7 @@ import sys
 import json
 import torch
 from safetensors.torch import save_file
-from transformers import CLIPProcessor,CLIPModel
+from transformers import CLIPProcessor,CLIPTextModel
 
 import logging
 # Turn off  stupid mesages from CLIPModel.load
@@ -41,18 +40,18 @@ def init():
     processor = CLIPProcessor.from_pretrained(clipsrc)
     print("done",file=sys.stderr)
     print("loading model from "+clipsrc,file=sys.stderr)
-    model = CLIPModel.from_pretrained(clipsrc)
+    model = CLIPTextModel.from_pretrained(clipsrc)
     print("done",file=sys.stderr)
 
     model = model.to(device)
 
-def standard_embed_calc(text):
+def cliptextmodel_embed_calc(text):
     inputs = processor(text=text, return_tensors="pt")
     inputs.to(device)
     with torch.no_grad():
-        text_features = model.get_text_features(**inputs)
-    embedding = text_features[0]
-    return embedding
+        outputs = model(**inputs)
+    embeddings = outputs.pooler_output
+    return embeddings
 
 
 init()
@@ -60,11 +59,15 @@ init()
 
 word = input("type a phrase to generate an embedding for: ")
 
-emb = standard_embed_calc(word)
-embs=emb.unsqueeze(0) # stupid matrix magic to make the cat work
+emb = cliptextmodel_embed_calc(word)
+#embs=emb.unsqueeze(0) # stupid matrix magic to make it the required shape
+embs=emb
 
 print("Shape of result = ",embs.shape)
+
 output = "generated.safetensors"
+if all(char.isalpha() for char in word):
+    output=f"{word}.safetensors"
 print(f"Saving to {output}...")
 save_file({"emb_params": embs}, output)