Instructions to use mapama247/fos with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mapama247/fos with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="mapama247/fos")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("mapama247/fos") model = AutoModelForSequenceClassification.from_pretrained("mapama247/fos") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8863f576d63a059273bbb7515a88685a4aeed014aa8fab874bee8af7208160f5
- Size of remote file:
- 2.48 kB
- SHA256:
- c977e870cd84212a10faad154616e0c5af4e2ac825e4f21da3ab262904d3c624
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.