Sentence Similarity
sentence-transformers
Safetensors
Transformers
xlm-roberta
feature-extraction
text-embeddings-inference
Instructions to use artificial-nerds/pmnet with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use artificial-nerds/pmnet with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("artificial-nerds/pmnet") 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 artificial-nerds/pmnet with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("artificial-nerds/pmnet") model = AutoModel.from_pretrained("artificial-nerds/pmnet", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| language: | |
| - multilingual | |
| - ar | |
| - bg | |
| - ca | |
| - cs | |
| - da | |
| - de | |
| - el | |
| - en | |
| - es | |
| - et | |
| - fa | |
| - fi | |
| - fr | |
| - gl | |
| - gu | |
| - he | |
| - hi | |
| - hr | |
| - hu | |
| - hy | |
| - id | |
| - it | |
| - ja | |
| - ka | |
| - ko | |
| - ku | |
| - lt | |
| - lv | |
| - mk | |
| - mn | |
| - mr | |
| - ms | |
| - my | |
| - nb | |
| - nl | |
| - pl | |
| - pt | |
| - ro | |
| - ru | |
| - sk | |
| - sl | |
| - sq | |
| - sr | |
| - sv | |
| - th | |
| - tr | |
| - uk | |
| - ur | |
| - vi | |
| license: apache-2.0 | |
| library_name: sentence-transformers | |
| tags: | |
| - sentence-transformers | |
| - feature-extraction | |
| - sentence-similarity | |
| - transformers | |
| language_bcp47: | |
| - fr-ca | |
| - pt-br | |
| - zh-cn | |
| - zh-tw | |
| pipeline_tag: sentence-similarity | |