Sentence Similarity
sentence-transformers
Safetensors
bert
feature-extraction
Generated from Trainer
dataset_size:4370
loss:CosineSimilarityLoss
text-embeddings-inference
Instructions to use VaggP/bge-fine-tuned with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
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] - Notebooks
- Google Colab
- Kaggle
Download modules.json from VaggP/bge-fine-tuned: direct link, hf CLI and curl.
- Browser
- Download file 349 Bytes
-
https://huggingface.co/VaggP/bge-fine-tuned/resolve/main/modules.json
- Command line
-
hf download hf://VaggP/bge-fine-tuned/modules.json
-
curl -L -o modules.json https://huggingface.co/VaggP/bge-fine-tuned/resolve/main/modules.json
349 Bytes
| [ | |
| { | |
| "idx": 0, | |
| "name": "0", | |
| "path": "", | |
| "type": "sentence_transformers.models.Transformer" | |
| }, | |
| { | |
| "idx": 1, | |
| "name": "1", | |
| "path": "1_Pooling", | |
| "type": "sentence_transformers.models.Pooling" | |
| }, | |
| { | |
| "idx": 2, | |
| "name": "2", | |
| "path": "2_Normalize", | |
| "type": "sentence_transformers.models.Normalize" | |
| } | |
| ] |