Sentence Similarity
sentence-transformers
Safetensors
Transformers
Norwegian
Norwegian Bokmål
Norwegian Nynorsk
feature-extraction
custom_code
Instructions to use tollefj/norbert3-multiloss-embedder with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use tollefj/norbert3-multiloss-embedder with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("tollefj/norbert3-multiloss-embedder", trust_remote_code=True) 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 tollefj/norbert3-multiloss-embedder with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("tollefj/norbert3-multiloss-embedder", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download 1_Pooling/config.json from tollefj/norbert3-multiloss-embedder: direct link, hf CLI and curl.
- Browser
- Download file 296 Bytes
-
https://huggingface.co/tollefj/norbert3-multiloss-embedder/resolve/main/1_Pooling/config.json
- Command line
-
hf download hf://tollefj/norbert3-multiloss-embedder/1_Pooling/config.json
-
curl -L -o config.json https://huggingface.co/tollefj/norbert3-multiloss-embedder/resolve/main/1_Pooling/config.json
296 Bytes
| { | |
| "word_embedding_dimension": 768, | |
| "pooling_mode_cls_token": false, | |
| "pooling_mode_mean_tokens": true, | |
| "pooling_mode_max_tokens": false, | |
| "pooling_mode_mean_sqrt_len_tokens": false, | |
| "pooling_mode_weightedmean_tokens": false, | |
| "pooling_mode_lasttoken": false, | |
| "include_prompt": true | |
| } |