Instructions to use hf-tiny-model-private/tiny-random-LEDForSequenceClassification 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-LEDForSequenceClassification 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-LEDForSequenceClassification")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("hf-tiny-model-private/tiny-random-LEDForSequenceClassification") model = AutoModelForSequenceClassification.from_pretrained("hf-tiny-model-private/tiny-random-LEDForSequenceClassification") - Notebooks
- Google Colab
- Kaggle
File size: 132 Bytes
fef7b71 | 1 2 3 4 | version https://git-lfs.github.com/spec/v1
oid sha256:9bbace9cadf0de8e98e67a26cfe7234f8b234b47ba8b56128a83812a3d2c346a
size 1229240
|