Instructions to use idsedykh/model1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use idsedykh/model1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="idsedykh/model1")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("idsedykh/model1") model = AutoModelForTokenClassification.from_pretrained("idsedykh/model1") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3350470cf0ffeb9f1c4acf67ce40ffadab859655df31039bd54fecef6875b446
- Size of remote file:
- 2.5 MB
- SHA256:
- 84907e9b30e8c0486ac9c63a94d21432f61e40393e6e46c7809d02e32967355c
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.