How to use crewdon/AICategoryMapping-multilingual-e5-small with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("crewdon/AICategoryMapping-multilingual-e5-small") sentences = [ "That is a happy person", "That is a happy dog", "That is a very happy person", "Today is a sunny day" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4]
How to use crewdon/AICategoryMapping-multilingual-e5-small with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("crewdon/AICategoryMapping-multilingual-e5-small") model = AutoModel.from_pretrained("crewdon/AICategoryMapping-multilingual-e5-small", device_map="auto")
https://huggingface.co/crewdon/AICategoryMapping-multilingual-e5-small/resolve/main/googleCategoryMapping20230829.csv
hf download hf://crewdon/AICategoryMapping-multilingual-e5-small/googleCategoryMapping20230829.csv
curl -L -o googleCategoryMapping20230829.csv https://huggingface.co/crewdon/AICategoryMapping-multilingual-e5-small/resolve/main/googleCategoryMapping20230829.csv
