Sentence Similarity
sentence-transformers
Safetensors
roberta
feature-extraction
Generated from Trainer
dataset_size:102645
loss:CosineSimilarityLoss
Eval Results (legacy)
Instructions to use tranhuudan-fullstack-ai-engineer/final_model_main with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use tranhuudan-fullstack-ai-engineer/final_model_main with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("tranhuudan-fullstack-ai-engineer/final_model_main") sentences = [ "Tổng thống Bulgaria cố gắng phá vỡ bế tắc bầu cử", "Maldives tổ chức bầu cử tổng thống mới", "Cháy rừng Oklahoma phá hủy nhà cửa - trong ảnh", "Một đang đi dọc theo một hồ bơi." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
Download 1_Pooling/config.json from tranhuudan-fullstack-ai-engineer/final_model_main: direct link, hf CLI and curl.
- Browser
- Download file 296 Bytes
-
https://huggingface.co/tranhuudan-fullstack-ai-engineer/final_model_main/resolve/main/1_Pooling/config.json
- Command line
-
hf download hf://tranhuudan-fullstack-ai-engineer/final_model_main/1_Pooling/config.json
-
curl -L -o config.json https://huggingface.co/tranhuudan-fullstack-ai-engineer/final_model_main/resolve/main/1_Pooling/config.json
296 Bytes
| { | |
| "word_embedding_dimension": 768, | |
| "pooling_mode_cls_token": false, | |
| "pooling_mode_mean_tokens": true, | |
| "pooling_mode_max_tokens": false, | |
| "pooling_mode_mean_sqrt_len_tokens": false, | |
| "pooling_mode_weightedmean_tokens": false, | |
| "pooling_mode_lasttoken": false, | |
| "include_prompt": true | |
| } |