Instructions to use ydshieh/tiny-random-BertForTokenClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ydshieh/tiny-random-BertForTokenClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="ydshieh/tiny-random-BertForTokenClassification")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("ydshieh/tiny-random-BertForTokenClassification") model = AutoModelForTokenClassification.from_pretrained("ydshieh/tiny-random-BertForTokenClassification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
#9 opened over 3 years ago
by
SFconvertbot
Update tiny models for BertForTokenClassification
#8 opened about 4 years ago
by
ydshieh
Update tiny models for BertForTokenClassification
#7 opened about 4 years ago
by
ydshieh
Update tiny models for BertForTokenClassification
#6 opened about 4 years ago
by
ydshieh
Update tiny models for BertForTokenClassification
#5 opened about 4 years ago
by
ydshieh
Update tiny models for BertForTokenClassification
#4 opened about 4 years ago
by
ydshieh
Update tiny models for BertForTokenClassification
#3 opened about 4 years ago
by
ydshieh
Update tiny models for BertForTokenClassification
#2 opened about 4 years ago
by
ydshieh
Update tiny models for BertForTokenClassification
#1 opened about 4 years ago
by
ydshieh