Instructions to use andreasmadsen/efficient_mlm_m0.15-801010 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use andreasmadsen/efficient_mlm_m0.15-801010 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="andreasmadsen/efficient_mlm_m0.15-801010")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("andreasmadsen/efficient_mlm_m0.15-801010") model = AutoModelForMaskedLM.from_pretrained("andreasmadsen/efficient_mlm_m0.15-801010", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 78cc6d5aaaf309ee44434d96d3b79074f29afa385ee5600b86fb13e62c3415b2
- Size of remote file:
- 1.63 GB
- SHA256:
- e453ca3929b55e21650fe504af3c5fc087b8e080db7730e126f25212827403cb
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.