Instructions to use doomnova/distilbert_system_A with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use doomnova/distilbert_system_A with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="doomnova/distilbert_system_A")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("doomnova/distilbert_system_A") model = AutoModelForTokenClassification.from_pretrained("doomnova/distilbert_system_A", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 11abace64c1a3e49ba9cd41a773bbaabc3833e70fd2e9c715749ea8a0b71573a
- Size of remote file:
- 261 MB
- SHA256:
- 0ee975ea43c2a4ee4adb112738ae55dc4f8e88725de5b1a3ad49fc5bdbc54d4f
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.