Instructions to use btan2/cappy-large with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use btan2/cappy-large with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="btan2/cappy-large")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("btan2/cappy-large") model = AutoModelForSequenceClassification.from_pretrained("btan2/cappy-large", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 135 Bytes
aed97f1 | 1 2 3 4 | version https://git-lfs.github.com/spec/v1
oid sha256:12c75d1559962148fbaeec6afebdd4657cdf2777fa12b36763c12ee5044ac4cd
size 1421573614
|