Sentence Similarity
sentence-transformers
Safetensors
Transformers
Dutch
bert
feature-extraction
text-embeddings-inference
Instructions to use clips/e5-small-trm with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use clips/e5-small-trm with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("clips/e5-small-trm") sentences = [ "The weather is lovely today.", "It's so sunny outside!", "He drove to the stadium." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [3, 3] - Transformers
How to use clips/e5-small-trm with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("clips/e5-small-trm") model = AutoModel.from_pretrained("clips/e5-small-trm", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model.safetensors from clips/e5-small-trm: direct link, hf CLI and curl.
- Browser
- Download file 163 MB
-
https://huggingface.co/clips/e5-small-trm/resolve/main/model.safetensors
- Command line
-
hf download hf://clips/e5-small-trm/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/clips/e5-small-trm/resolve/main/model.safetensors
163 MB
- Xet hash:
- 662b772988f4a4fc79e0598c1f537968e319e582366894647fa0d11acbbbe73f
- Size of remote file:
- 163 MB
- SHA256:
- 091687d7010e09adfb4dee400ad1f469efa60f0f7c1e21619932440c454f73f0
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