Instructions to use hf-internal-testing/tiny-bert-for-token-classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-bert-for-token-classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="hf-internal-testing/tiny-bert-for-token-classification")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-bert-for-token-classification") model = AutoModelForTokenClassification.from_pretrained("hf-internal-testing/tiny-bert-for-token-classification") - Inference
- Notebooks
- Google Colab
- Kaggle
# Load model directly
from transformers import AutoTokenizer, AutoModelForTokenClassification
tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-bert-for-token-classification")
model = AutoModelForTokenClassification.from_pretrained("hf-internal-testing/tiny-bert-for-token-classification")Quick Links
YAML Metadata Warning:empty or missing yaml metadata in repo card
Check out the documentation for more information.
Small model used as a token-classification to enable fast tests on that pipeline.
- Downloads last month
- 32,764
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="hf-internal-testing/tiny-bert-for-token-classification")