Sentence Similarity
sentence-transformers
Safetensors
English
bert
task-oriented-dialogues
dialog-flow
text-embeddings-inference
Instructions to use sergioburdisso/dialog2flow-joint-bert-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use sergioburdisso/dialog2flow-joint-bert-base with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("sergioburdisso/dialog2flow-joint-bert-base") sentences = [ "your phone please", "please get their phone number", "okay can i get your phone number please to make that booking", "okay can i please get your id number" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
Download 1_Pooling/config.json from sergioburdisso/dialog2flow-joint-bert-base: direct link, hf CLI and curl.
- Browser
- Download file 270 Bytes
-
https://huggingface.co/sergioburdisso/dialog2flow-joint-bert-base/resolve/main/1_Pooling/config.json
- Command line
-
hf download hf://sergioburdisso/dialog2flow-joint-bert-base/1_Pooling/config.json
-
curl -L -o config.json https://huggingface.co/sergioburdisso/dialog2flow-joint-bert-base/resolve/main/1_Pooling/config.json
270 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 | |
| } |