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
Download tokenizer.json from novelcore/chimera-vdr: direct link, hf CLI and curl.
- Browser
- Download file 17.2 MB
-
https://huggingface.co/novelcore/chimera-vdr/resolve/main/tokenizer.json
- Command line
-
hf download hf://novelcore/chimera-vdr/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/novelcore/chimera-vdr/resolve/main/tokenizer.json
17.2 MB
- Xet hash:
- 82647399a6b2281651c26a7500e1c6d8348906d761636f8b80f4e77227eb11ca
- Size of remote file:
- 17.2 MB
- SHA256:
- 0fb8bdddbd4c4ffa55e51d5b0393611e3df49dd86a31189ef5dcb750cf3da399
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