Sentence Similarity
sentence-transformers
Safetensors
roberta
feature-extraction
Generated from Trainer
dataset_size:5749
loss:CosineSimilarityLoss
Eval Results (legacy)
Instructions to use tranhuudan-fullstack-ai-engineer/model_stage3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use tranhuudan-fullstack-ai-engineer/model_stage3 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("tranhuudan-fullstack-ai-engineer/model_stage3") sentences = [ "trắng và nâu đang chạy nhanh qua đám cỏ.", "Một chiếc máy bay trên bầu trời.", "trắng lớn đang chạy trên cỏ.", "Hai con đại bàng đang đậu trên cành cây." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
Download bpe.codes from tranhuudan-fullstack-ai-engineer/model_stage3: direct link, hf CLI and curl.
- Browser
- Download file 1.14 MB
-
https://huggingface.co/tranhuudan-fullstack-ai-engineer/model_stage3/resolve/main/bpe.codes
- Command line
-
hf download hf://tranhuudan-fullstack-ai-engineer/model_stage3/bpe.codes
-
curl -L -o bpe.codes https://huggingface.co/tranhuudan-fullstack-ai-engineer/model_stage3/resolve/main/bpe.codes
1.14 MB
File too large to display, you can check the raw version instead.