Instructions to use hf-tiny-model-private/tiny-random-DebertaForSequenceClassification 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-DebertaForSequenceClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="hf-tiny-model-private/tiny-random-DebertaForSequenceClassification")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("hf-tiny-model-private/tiny-random-DebertaForSequenceClassification") model = AutoModelForSequenceClassification.from_pretrained("hf-tiny-model-private/tiny-random-DebertaForSequenceClassification") - Notebooks
- Google Colab
- Kaggle
File size: 131 Bytes
b090296 | 1 2 3 4 | version https://git-lfs.github.com/spec/v1
oid sha256:14f0a29dcfad94992c1a8efca6118cc2a98795e5fc7dab8d32c780d603c35fec
size 350908
|