Sentence Similarity
sentence-transformers
PyTorch
Transformers
English
t5
text-embedding
embeddings
information-retrieval
beir
text-classification
language-model
text-clustering
text-semantic-similarity
text-evaluation
prompt-retrieval
text-reranking
feature-extraction
English
Sentence Similarity
natural_questions
ms_marco
fever
hotpot_qa
mteb
Eval Results (legacy)
Instructions to use hkunlp/instructor-large with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use hkunlp/instructor-large with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("hkunlp/instructor-large") 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 hkunlp/instructor-large with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("hkunlp/instructor-large") model = AutoModel.from_pretrained("hkunlp/instructor-large") - Notebooks
- Google Colab
- Kaggle
model works fine on windows but segfaults on macos
#30
by AminnO - opened
"embedding_model = HuggingFaceEmbeddings(model_name="hkunlp/instructor-large")" gives this error "model.safetensors: 4%|▉ | 52.4M/1.34G [00:00<?, ?B/s][1] 1653 segmentation fault python data_em.py
/opt/homebrew/Cellar/python@3.13/3.13.3/Frameworks/Python.framework/Versions/3.13/lib/python3.13/multiprocessing/resource_tracker.py:301: UserWarning: resource_tracker: There appear to be 1 leaked semaphore objects to clean up at shutdown: {'/loky-1653-nr87v7or'}
warnings.warn(".