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Traceback (most recent call last):
File "O:\AI\stable-diffusion-webui\venv\lib\site-packages\gradio\routes.py", line 321, in run_predict
output = await app.blocks.process_api(
File "O:\AI\stable-diffusion-webui\venv\lib\site-packages\gradio\blocks.py", line 1015, in process_api
result = await self.call_function(fn_index, inputs, iterator, request)
File "O:\AI\stable-diffusion-webui\venv\lib\site-packages\gradio\blocks.py", line 856, in call_function
prediction = await anyio.to_thread.run_sync(
File "O:\AI\stable-diffusion-webui\venv\lib\site-packages\anyio\to_thread.py", line 31, in run_sync
return await get_asynclib().run_sync_in_worker_thread(
File "O:\AI\stable-diffusion-webui\venv\lib\site-packages\anyio\_backends\_asyncio.py", line 937, in run_sync_in_worker_thread
return await future
File "O:\AI\stable-diffusion-webui\venv\lib\site-packages\anyio\_backends\_asyncio.py", line 867, in run
result = context.run(func, *args)
File "O:\AI\stable-diffusion-webui\extensions\stable-diffusion-webui-embedding-editor\scripts\embedding_editor.py", line 251, in save_embedding_weights
save_embedding(embedding, checkpoint, embedding_name, filename, remove_cached_checksum=True)
TypeError: save_embedding() missing 1 required positional argument: 'filename'
Though, first, I did try to select vector 2 on said embedding, which only has 2 vectors (0 and 1), which resulted in such error (which is understandable):
File "O:\AI\stable-diffusion-webui\extensions\stable-diffusion-webui-embedding-editor\scripts\embedding_editor.py", line 195, in select_embedding
vec = embedding.vec[int(vector_num)]
IndexError: index 2 is out of bounds for dimension 0 with size 2
Should I try to hardcode some filename, while not trying to reload the whole UI? I don't want to lose the changes I've made... :)
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