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 merges.txt from machinev/model: direct link, hf CLI and curl.
- Browser
- Download file 525 kB
-
https://huggingface.co/machinev/model/resolve/main/merges.txt
- Command line
-
hf download hf://machinev/model/merges.txt
-
curl -L -o merges.txt https://huggingface.co/machinev/model/resolve/main/merges.txt
525 kB
File too large to display, you can check the raw version instead.