Text Ranking
Transformers
PyTorch
Safetensors
multilingual
llama_bidirec
text-classification
text
reranker
cross-encoder
retrieval
semantic-search
custom_code
text-embeddings-inference
Instructions to use nvidia/llama-nemotron-rerank-1b-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nvidia/llama-nemotron-rerank-1b-v2 with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModelForSequenceClassification model = AutoModelForSequenceClassification.from_pretrained("nvidia/llama-nemotron-rerank-1b-v2", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Add rope_theta to rope_scaling for transformers 5.4+ compatibility
#14
by oliverholworthy - opened
transformers==5.4.0 validates that rope_theta is present inside rope_scaling before the migration from the top-level field runs, causing a KeyError when loading the config without trust_remote_code=True. Adds rope_theta inside rope_scaling while keeping the top-level value for backwards compatibility with transformers v4.
oliverholworthy changed pull request title from dd rope_theta to rope_scaling for transformers 5.4+ compatibility to Add rope_theta to rope_scaling for transformers 5.4+ compatibility
oliverholworthy changed pull request status to open
oliverholworthy changed pull request status to merged