How to use VaggP/bge-fine-tuned with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("VaggP/bge-fine-tuned") sentences = [ "\nConstruct: Recognise a linear graph from its shape\nSubject: Finding the Gradient and Intercept of a Line from the Equation\nQuestion: Use a graphing program (e.g. Desmos) to plot the following pairs of functions.\n\\[\ny=3 \\text { and } y=-2\n\\]\n\nTom says both functions are linear\n\nKatie says both functions are vertical lines\n\nWho is correct?\nIncorrect Answer: Neither is correct\nCorrect Answer: Only\nTom\n", "Believes the coefficent of x in an expanded quadratic comes from multiplying the two numbers in the brackets", "Does not know the properties of a linear graph", "Misremembers the quadratic formula" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4]
https://huggingface.co/VaggP/bge-fine-tuned/resolve/main/tokenizer.json
hf download hf://VaggP/bge-fine-tuned/tokenizer.json
curl -L -o tokenizer.json https://huggingface.co/VaggP/bge-fine-tuned/resolve/main/tokenizer.json
