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:
- f88bef22843900ee5715a55b206211508e4c130ef16583cf011905f7e4fe2c19
- Size of remote file:
- 2.74 kB
- SHA256:
- bfaf5488385767f5528ab77b13ee423a9a311a2700f88b57c84255addc6bd079
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.