Instructions to use tmanabe/ir100-dogfooding-embedding with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tmanabe/ir100-dogfooding-embedding with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="tmanabe/ir100-dogfooding-embedding")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("tmanabe/ir100-dogfooding-embedding") model = AutoModelForMaskedLM.from_pretrained("tmanabe/ir100-dogfooding-embedding") - Notebooks
- Google Colab
- Kaggle
A mock model trained with https://github.com/amazon-science/esci-data
- Downloads last month
- 3