Sentence Similarity
sentence-transformers
PyTorch
TensorFlow
ONNX
Safetensors
OpenVINO
Transformers
mpnet
feature-extraction
text-embeddings-inference
Instructions to use sentence-transformers/nli-mpnet-base-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use sentence-transformers/nli-mpnet-base-v2 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("sentence-transformers/nli-mpnet-base-v2") 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 sentence-transformers/nli-mpnet-base-v2 with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("sentence-transformers/nli-mpnet-base-v2") model = AutoModel.from_pretrained("sentence-transformers/nli-mpnet-base-v2", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
Commercial Availability
#1
by yotkovv-recourse - opened
Hello everyone,
After seeing Nils Reimers's Twitter post at https://twitter.com/Nils_Reimers/status/1488438810824396800 , I am wondering if this model here is available for commercial use?
It has the Apache 2.0 license and does not seem to be trained on private/research-only datasets.
What do you think?
Regards,
Vlad