Sentence Similarity
sentence-transformers
Safetensors
clip
feature-extraction
Generated from Trainer
dataset_size:12
loss:MultipleNegativesRankingLoss
Eval Results (legacy)
Instructions to use machinev/model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use machinev/model with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("machinev/model") sentences = [ "the main power cable is connected with LPT ", "the main power cable is connected with LPT ", "the main power cable is connected with LPT ", "/content/sample_data/images/LPT (2).jpeg" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
Download config_sentence_transformers.json from machinev/model: direct link, hf CLI and curl.
- Browser
- Download file 205 Bytes
-
https://huggingface.co/machinev/model/resolve/main/config_sentence_transformers.json
- Command line
-
hf download hf://machinev/model/config_sentence_transformers.json
-
curl -L -o config_sentence_transformers.json https://huggingface.co/machinev/model/resolve/main/config_sentence_transformers.json
205 Bytes
| { | |
| "__version__": { | |
| "sentence_transformers": "3.4.1", | |
| "transformers": "4.48.3", | |
| "pytorch": "2.5.1+cu124" | |
| }, | |
| "prompts": {}, | |
| "default_prompt_name": null, | |
| "similarity_fn_name": "cosine" | |
| } |