Instructions to use hf-tiny-model-private/tiny-random-AlbertForTokenClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-tiny-model-private/tiny-random-AlbertForTokenClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="hf-tiny-model-private/tiny-random-AlbertForTokenClassification")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("hf-tiny-model-private/tiny-random-AlbertForTokenClassification") model = AutoModelForTokenClassification.from_pretrained("hf-tiny-model-private/tiny-random-AlbertForTokenClassification") - Notebooks
- Google Colab
- Kaggle
File size: 133 Bytes
2810c72 | 1 2 3 4 | version https://git-lfs.github.com/spec/v1
oid sha256:352c458dc04d0d4e1e76007e0f1d790c409e6b00c061d96a245ff4f1b81144a2
size 15865936
|