OSError: Can't load tokenizer for '/Users/wschrep/.cache/huggingface/hub/models--sentence-transformers--all-MiniLM-L6-v2/snapshots/8b3219a92973c328a8e22fadcfa821b5dc75636a'. If you were trying to load it from 'https://huggingface.co/models', make sure you don't have a local directory with the same name. Otherwise, make sure '/Users/wschrep/.cache/huggingface/hub/models--sentence-transformers--all-MiniLM-L6-v2/snapshots/8b3219a92973c328a8e22fadcfa821b5dc75636a' is the correct path to a directory containing all relevant files for a BertTokenizerFast tokenizer.
[1]    33382 segmentation fault  ./start.sh

 File "/Users/wschrep/llmWork/open-webui/backend/main.py", line 43, in <module>
    from apps.rag.main import app as rag_app
  File "/Users/wschrep/llmWork/open-webui/backend/apps/rag/main.py", line 210, in <module>
    update_embedding_model(
  File "/Users/wschrep/llmWork/open-webui/backend/apps/rag/main.py", line 187, in update_embedding_model
    app.state.sentence_transformer_ef = sentence_transformers.SentenceTransformer(
  File "/Users/wschrep/llmWork/open-webui/backend/python_env/lib/python3.9/site-packages/sentence_transformers/SentenceTransformer.py", line 197, in __init__
    modules = self._load_sbert_model(
  File "/Users/wschrep/llmWork/open-webui/backend/python_env/lib/python3.9/site-packages/sentence_transformers/SentenceTransformer.py", line 1296, in _load_sbert_model
    module = Transformer(model_name_or_path, cache_dir=cache_folder, **kwargs)
  File "/Users/wschrep/llmWork/open-webui/backend/python_env/lib/python3.9/site-packages/sentence_transformers/models/Transformer.py", line 38, in __init__
    self.tokenizer = AutoTokenizer.from_pretrained(
  File "/Users/wschrep/llmWork/open-webui/backend/python_env/lib/python3.9/site-packages/transformers/models/auto/tokenization_auto.py", line 899, in from_pretrained
    return tokenizer_class_fast.from_pretrained(pretrained_model_name_or_path, *inputs, **kwargs)
  File "/Users/wschrep/llmWork/open-webui/backend/python_env/lib/python3.9/site-packages/transformers/tokenization_utils_base.py", line 2094, in from_pretrained