Model Details
Full Model IDdatasocietyco/bge-base-en-v1.5-course-recommender-v5
Pipeline / Tasksentence-similarity
Librarysentence-transformers
Downloads (all-time)4.0M
Likes23
Last Modified1/9/2025
Author / Orgdatasocietyco
PrivateNo — public
⚡ Quick Usage (Python)
Using the 🤗 Transformers library. Install with pip install transformers
from transformers import pipeline
# Load the model
pipe = pipeline("sentence-similarity", model="datasocietyco/bge-base-en-v1.5-course-recommender-v5")
# Run inference
result = pipe("Your input here")
print(result)🏷️ Tags
sentence-transformerssafetensorsbertsentence-similarityfeature-extractiongenerated_from_trainerdataset_size:45loss:MultipleNegativesRankingLossarxiv:1908.10084arxiv:1705.00652base_model:BAAI/bge-base-en-v1.5base_model:finetune:BAAI/bge-base-en-v1.5text-embeddings-inferenceendpoints_compatibledeploy:azureregion:us
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Access model files, inference API, and full documentation on Hugging Face.
Open on Hugging Face →Browse Model Files ↗← Browse All Models🤖 Task: sentence-similarity
This model is designed for the sentence-similarity task. Explore more models for this use case.
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⬇ Downloads4.0M
❤️ Community Likes23
🛠️ Requirements
- →Install: pip install sentence-transformers
- →Python 3.8+ recommended for Transformers.
- →GPU (CUDA) speeds up inference significantly.
- →Use model.half() for fp16 on limited VRAM.