Instructions to use intelcomp/ipc_level1_F with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use intelcomp/ipc_level1_F with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="intelcomp/ipc_level1_F")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("intelcomp/ipc_level1_F") model = AutoModelForSequenceClassification.from_pretrained("intelcomp/ipc_level1_F") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 91ee988a245e0b754c3305d834d0e9d8fbe22df08d7f0144d149e8d03f667feb
- Size of remote file:
- 15.5 kB
- SHA256:
- a4e90f1345986502ffb3f500ea6d1b484187c5f83a6f051ae2d30f98cc82db9a
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.