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 special_tokens_map.json from novelcore/model8: direct link, hf CLI and curl.
- Browser
- Download file 239 Bytes
-
https://huggingface.co/novelcore/model8/resolve/main/special_tokens_map.json
- Command line
-
hf download hf://novelcore/model8/special_tokens_map.json
-
curl -L -o special_tokens_map.json https://huggingface.co/novelcore/model8/resolve/main/special_tokens_map.json
239 Bytes
| {"bos_token": "<s>", "eos_token": "</s>", "unk_token": "[UNK]", "sep_token": "</s>", "pad_token": "<pad>", "cls_token": "<s>", "mask_token": {"content": "<mask>", "single_word": false, "lstrip": true, "rstrip": false, "normalized": false}} |