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:
# Load model directly from transformers import AutoTokenizer, AutoModelForMultimodalLM tokenizer = AutoTokenizer.from_pretrained("novelcore/model8") model = AutoModelForMultimodalLM.from_pretrained("novelcore/model8") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- bb01445067ecd72953a30eadde050ec56b1c08736c4022ff96791fb7b53d4b9b
- Size of remote file:
- 438 MB
- SHA256:
- 2805a066aca73c77f49fd33a2c77926e3e1d620d8eba69a1607d98d4fcea1aab
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