Actually works properly
Browse filesprior versions were generated using CLIPModel.
Turns out thats the WRONG model. Now using the same code that SD actually uses: CLIPTextModel
- generate-embedding.py +12 -9
generate-embedding.py
CHANGED
@@ -3,7 +3,6 @@
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""" Work in progress
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NB: This is COMPLETELY DIFFERENT from "generate-embeddings.py"!!!
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-
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Plan:
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Take input for a single word or phrase.
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Generate a embedding file, "generated.safetensors"
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@@ -20,7 +19,7 @@ import sys
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import json
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import torch
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from safetensors.torch import save_file
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-
from transformers import CLIPProcessor,
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import logging
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# Turn off stupid mesages from CLIPModel.load
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@@ -41,18 +40,18 @@ def init():
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processor = CLIPProcessor.from_pretrained(clipsrc)
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print("done",file=sys.stderr)
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print("loading model from "+clipsrc,file=sys.stderr)
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model =
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print("done",file=sys.stderr)
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model = model.to(device)
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-
def
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inputs = processor(text=text, return_tensors="pt")
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inputs.to(device)
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with torch.no_grad():
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-
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-
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return
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init()
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@@ -60,11 +59,15 @@ init()
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word = input("type a phrase to generate an embedding for: ")
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-
emb =
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embs=emb.unsqueeze(0) # stupid matrix magic to make the
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print("Shape of result = ",embs.shape)
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output = "generated.safetensors"
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print(f"Saving to {output}...")
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save_file({"emb_params": embs}, output)
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""" Work in progress
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NB: This is COMPLETELY DIFFERENT from "generate-embeddings.py"!!!
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|
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Plan:
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Take input for a single word or phrase.
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Generate a embedding file, "generated.safetensors"
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import json
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import torch
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from safetensors.torch import save_file
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+
from transformers import CLIPProcessor,CLIPTextModel
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import logging
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# Turn off stupid mesages from CLIPModel.load
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processor = CLIPProcessor.from_pretrained(clipsrc)
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print("done",file=sys.stderr)
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print("loading model from "+clipsrc,file=sys.stderr)
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model = CLIPTextModel.from_pretrained(clipsrc)
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print("done",file=sys.stderr)
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model = model.to(device)
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+
def cliptextmodel_embed_calc(text):
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inputs = processor(text=text, return_tensors="pt")
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inputs.to(device)
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with torch.no_grad():
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outputs = model(**inputs)
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embeddings = outputs.pooler_output
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return embeddings
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init()
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word = input("type a phrase to generate an embedding for: ")
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emb = cliptextmodel_embed_calc(word)
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#embs=emb.unsqueeze(0) # stupid matrix magic to make it the required shape
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embs=emb
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print("Shape of result = ",embs.shape)
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output = "generated.safetensors"
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if all(char.isalpha() for char in word):
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output=f"{word}.safetensors"
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print(f"Saving to {output}...")
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save_file({"emb_params": embs}, output)
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