Instructions to use Dauka-transformers/BERT_word2vec with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Dauka-transformers/BERT_word2vec with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="Dauka-transformers/BERT_word2vec")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("Dauka-transformers/BERT_word2vec") model = AutoModelForMaskedLM.from_pretrained("Dauka-transformers/BERT_word2vec", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 133 Bytes
35e81b2 | 1 2 3 4 | version https://git-lfs.github.com/spec/v1
oid sha256:77743a0923b26a8b87ed0d8d8f7834e33c817308658697f35a93d8c2668af7d0
size 19451402
|