Instructions to use rlhn/e5-base-default-680K with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use rlhn/e5-base-default-680K with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="rlhn/e5-base-default-680K")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("rlhn/e5-base-default-680K") model = AutoModel.from_pretrained("rlhn/e5-base-default-680K", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Improve model card with paper information and usage details
#1
by nielsr HF Staff - opened
This PR updates the model card for the model by:
- Adding basic details (description, authors)
- Adding example usage
- Linking to Github code
- Adding information about training and evaluation
- Adding citation information
- Setting the pipeline tag to feature-extraction