Sentence Similarity
sentence-transformers
PyTorch
TensorFlow
ONNX
Safetensors
OpenVINO
Transformers
mpnet
feature-extraction
text-embeddings-inference
Instructions to use novelcore/model8 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use novelcore/model8 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("novelcore/model8") 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 novelcore/model8 with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("novelcore/model8") model = AutoModel.from_pretrained("novelcore/model8", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model.safetensors from novelcore/model8: direct link, hf CLI and curl.
- Browser
- Download file 438 MB
-
https://huggingface.co/novelcore/model8/resolve/main/model.safetensors
- Command line
-
hf download hf://novelcore/model8/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/novelcore/model8/resolve/main/model.safetensors
438 MB
- Xet hash:
- 6ef98607fce461434f19b8eafa71e006cbcfafb4e80d713eef4e160594455783
- Size of remote file:
- 438 MB
- SHA256:
- 5fc2279bd6e503ca3543197b4ef00b615d87eebd02490f8c108aa3f35d7b705d
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