Instructions to use intelcomp/fos_level0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use intelcomp/fos_level0 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="intelcomp/fos_level0")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("intelcomp/fos_level0") model = AutoModelForSequenceClassification.from_pretrained("intelcomp/fos_level0") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 006d79bc1050a3d35c48f999be70ea2fa6c83c54156f0ef372fea6ecba5bc81b
- Size of remote file:
- 1.42 GB
- SHA256:
- 904c4b71bbf089ea7864757c877c2950671ae6cc75d2f95e2f48e00a8586a91a
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.