Instructions to use sominw/redhot_ctx_encoder with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sominw/redhot_ctx_encoder with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="sominw/redhot_ctx_encoder")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("sominw/redhot_ctx_encoder") model = AutoModelForMaskedLM.from_pretrained("sominw/redhot_ctx_encoder") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 94ed0e69bf415b6fad215188a6477fae013ae3ec54c456d9afd34809cb847769
- Size of remote file:
- 443 MB
- SHA256:
- 2a72746ccd1aeb57ba99f2dff336ef3c421c3d398f2c432cb1b5714ce1145f7c
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.