Text Generation
sentence-transformers
Indonesian
English
chatbot
retrieval
hybrid-search
bm25
tfidf
sbert
mpnet
use
fuzzy-matching
indonesian
english
conversational
context-aware
multilingual
caca
Eval Results (legacy)
Instructions to use Lyon28/Caca-Chatbot-V2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use Lyon28/Caca-Chatbot-V2 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("Lyon28/Caca-Chatbot-V2") sentences = [ "The weather is lovely today.", "It's so sunny outside!", "He drove to the stadium." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [3, 3] - Notebooks
- Google Colab
- Kaggle
| { | |
| "\\b(halo|hai|hello|hi|hey)\\b": "greeting", | |
| "\\b(siapa|who|nama|name)\\b.*\\b(kamu|you|anda|lu)\\b": "identity", | |
| "\\b(terima kasih|thanks|thank you|thx|makasih)\\b": "thanks", | |
| "\\b(bye|dadah|selamat tinggal|goodbye)\\b": "goodbye", | |
| "\\b(apa|what|apaan)\\b.*\\b(itu|is|that)\\b": "definition", | |
| "\\b(bagaimana|how|gimana|caranya)\\b": "how_to", | |
| "\\b(kenapa|why|mengapa|knp)\\b": "why", | |
| "\\b(dimana|where|mana)\\b": "where", | |
| "\\b(kapan|when|jam)\\b": "when", | |
| "\\b(bisa|can|could|boleh)\\b": "capability", | |
| "\\b(tolong|help|bantu|bantuan)\\b": "help" | |
| } |