Sentence Similarity
sentence-transformers
Safetensors
Transformers
multilingual
llama_nemotron_vl
feature-extraction
retrieval
visual document retrieval
vlm embedding
page image embedding
text embedding
semantic search
question-answering retrieval
rag
custom_code
Instructions to use novelcore/chimera-vdr with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use novelcore/chimera-vdr with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("novelcore/chimera-vdr", trust_remote_code=True) 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 novelcore/chimera-vdr with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("novelcore/chimera-vdr", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
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