Instructions to use AlanRobotics/my_awesome_wnut_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AlanRobotics/my_awesome_wnut_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="AlanRobotics/my_awesome_wnut_model")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("AlanRobotics/my_awesome_wnut_model") model = AutoModelForTokenClassification.from_pretrained("AlanRobotics/my_awesome_wnut_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 914a0ed25ff58c0268405d48967b4a45d22ddc9a4d7b64be26b80273f3d99f6d
- Size of remote file:
- 5.65 kB
- SHA256:
- 45ccdec72ea775ed86727433961248e29f1b1668d56050d68fecd694400a1103
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.