Token Classification
Transformers
PyTorch
English
bert
fill-mask
bert-base-cased
biodiversity
sequence-classification
Instructions to use NoYo25/BiodivBERT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use NoYo25/BiodivBERT with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="NoYo25/BiodivBERT")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("NoYo25/BiodivBERT") model = AutoModelForMaskedLM.from_pretrained("NoYo25/BiodivBERT") - Notebooks
- Google Colab
- Kaggle
File size: 129 Bytes
f4a00ff | 1 2 3 4 | version https://git-lfs.github.com/spec/v1
oid sha256:04ed0483362194e67a2d52d6a1a6d7cd93f04dc5a8464e72a20a80ee4473a782
size 3055
|