Instructions to use btk/output_bert_uncased with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use btk/output_bert_uncased with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="btk/output_bert_uncased")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("btk/output_bert_uncased") model = AutoModelForMaskedLM.from_pretrained("btk/output_bert_uncased", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 134 Bytes
2eed689 | 1 2 3 4 | version https://git-lfs.github.com/spec/v1
oid sha256:300ad809d140bbb5206bd32201d55d01864228a52f1036f26d9396f1457b0d97
size 440468442
|