Instructions to use hf-tiny-model-private/tiny-random-SqueezeBertForTokenClassification 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-SqueezeBertForTokenClassification 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-SqueezeBertForTokenClassification")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("hf-tiny-model-private/tiny-random-SqueezeBertForTokenClassification") model = AutoModelForTokenClassification.from_pretrained("hf-tiny-model-private/tiny-random-SqueezeBertForTokenClassification") - Notebooks
- Google Colab
- Kaggle
File size: 131 Bytes
c723fca | 1 2 3 4 | version https://git-lfs.github.com/spec/v1
oid sha256:9f2aecca23247a5a5e79b502ed1550829047eeecac50f1d3b80ba49f42d5302f
size 347135
|