How to use adiikj/tradexcel-assistant-encoder with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("adiikj/tradexcel-assistant-encoder") sentences = [ "That is a happy person", "That is a happy dog", "That is a very happy person", "Today is a sunny day" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4]
How to use adiikj/tradexcel-assistant-encoder with Transformers.js:
// npm i @huggingface/transformers import { pipeline } from '@huggingface/transformers'; // Allocate pipeline const pipe = await pipeline('feature-extraction', 'adiikj/tradexcel-assistant-encoder');
https://huggingface.co/adiikj/tradexcel-assistant-encoder/resolve/main/tokenizer.json
hf download hf://adiikj/tradexcel-assistant-encoder/tokenizer.json
curl -L -o tokenizer.json https://huggingface.co/adiikj/tradexcel-assistant-encoder/resolve/main/tokenizer.json
