Text Ranking
sentence-transformers
Safetensors
Transformers
mistral3
text-classification
reranker
cross-encoder
visual-document-retrieval
multimodal reranking
semantic-search
rag
vllm
custom_code
Instructions to use nvidia/Nemotron-3.5-Rerank-8B-BF16 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use nvidia/Nemotron-3.5-Rerank-8B-BF16 with sentence-transformers:
from sentence_transformers import CrossEncoder model = CrossEncoder("nvidia/Nemotron-3.5-Rerank-8B-BF16", trust_remote_code=True) query = "Which planet is known as the Red Planet?" passages = [ "Venus is often called Earth's twin because of its similar size and proximity.", "Mars, known for its reddish appearance, is often referred to as the Red Planet.", "Jupiter, the largest planet in our solar system, has a prominent red spot.", "Saturn, famous for its rings, is sometimes mistaken for the Red Planet." ] scores = model.predict([(query, passage) for passage in passages]) print(scores) - Transformers
How to use nvidia/Nemotron-3.5-Rerank-8B-BF16 with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForSequenceClassification processor = AutoProcessor.from_pretrained("nvidia/Nemotron-3.5-Rerank-8B-BF16", trust_remote_code=True) model = AutoModelForSequenceClassification.from_pretrained("nvidia/Nemotron-3.5-Rerank-8B-BF16", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
Yesterday
-
docs: validate reranking examples with Transformers 5.20.0
Unverified signatureSigned-off-by: Oliver Holworthy <oliverholworthy@users.noreply.huggingface.co>c0dc331
2 days ago
-
fix broken link in bias table
Verified signature2c69d2f -
Upload folder using huggingface_hub
Verified signature708e844 -
initial commit
Verified signature90ec0a8