Sentence Similarity
sentence-transformers
PyTorch
Safetensors
bert
feature-extraction
text-embeddings-inference
Instructions to use wt3639/EduGBERT_CourseRec with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use wt3639/EduGBERT_CourseRec with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("wt3639/EduGBERT_CourseRec") 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] - Notebooks
- Google Colab
- Kaggle
Download config_sentence_transformers.json from wt3639/EduGBERT_CourseRec: direct link, hf CLI and curl.
- Browser
- Download file 171 Bytes
-
https://huggingface.co/wt3639/EduGBERT_CourseRec/resolve/main/config_sentence_transformers.json
- Command line
-
hf download hf://wt3639/EduGBERT_CourseRec/config_sentence_transformers.json
-
curl -L -o config_sentence_transformers.json https://huggingface.co/wt3639/EduGBERT_CourseRec/resolve/main/config_sentence_transformers.json
171 Bytes
| { | |
| "__version__": { | |
| "sentence_transformers": "2.7.0", | |
| "transformers": "4.34.1", | |
| "pytorch": "2.2.0+cu121" | |
| }, | |
| "prompts": {}, | |
| "default_prompt_name": null | |
| } |