Instructions to use ianssens/e5-model-rag-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ianssens/e5-model-rag-v2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="ianssens/e5-model-rag-v2")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("ianssens/e5-model-rag-v2") model = AutoModel.from_pretrained("ianssens/e5-model-rag-v2") - Notebooks
- Google Colab
- Kaggle
Model Card
๐ Fine-Tuned Model from AI Talent Hub Hackathon
This model was fine-tuned during the AI Talent Hub Hackathon on a custom-generated dataset. The base model was fine-tuned to improve its performance on specific tasks related to "semantic search". It's second version of the model.
Model Details
Model Description
Train Dataset
34k - ['queries', 'corpus', 'relevant_docs', 'mode']
Split Info
chunk_size=512 chunk_overlap=20
- Developed by: ianssens
- Model type: text embedding
- Language(s) (NLP): Russian
- License: MIT
- Finetuned from model [optional]: e5-large
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