Sentence Similarity
sentence-transformers
PyTorch
Transformers
bert
feature-extraction
text-embeddings-inference
Instructions to use crewdon/AICategoryMapping-multilingual-e5-small with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
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] - Transformers
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") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from crewdon/AICategoryMapping-multilingual-e5-small: direct link, hf CLI and curl.
- Browser
- Download file 471 MB
-
https://huggingface.co/crewdon/AICategoryMapping-multilingual-e5-small/resolve/refs%2Fpr%2F1/pytorch_model.bin
- Command line
-
hf download hf://crewdon/AICategoryMapping-multilingual-e5-small@refs/pr/1/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/crewdon/AICategoryMapping-multilingual-e5-small/resolve/refs%2Fpr%2F1/pytorch_model.bin
471 MB
- Xet hash:
- c362d87fa5420e3e2ada15c27e29246df41e553f91777dd2f35f137407071ac9
- Size of remote file:
- 471 MB
- SHA256:
- 58ceb0ab4fc94a7917ad3291bbe4b74b67f61e9a3f4a5ef1bc921407bc2bb7d9
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