Instructions to use Shushant/ApplicantTrackingSystemBERT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Shushant/ApplicantTrackingSystemBERT with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="Shushant/ApplicantTrackingSystemBERT")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("Shushant/ApplicantTrackingSystemBERT") model = AutoModelForMaskedLM.from_pretrained("Shushant/ApplicantTrackingSystemBERT", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 210e4b7f40603d2ca9b01102eb73a886894c24df9248aa4b8e0be0ae93e99b08
- Size of remote file:
- 438 MB
- SHA256:
- 0bcfb82ac1025989135914089d49b922452cd1cd457b217ea6569a23116e96fb
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.