Instructions to use yehoshuadiller/my_wnut_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use yehoshuadiller/my_wnut_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="yehoshuadiller/my_wnut_model")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("yehoshuadiller/my_wnut_model") model = AutoModelForTokenClassification.from_pretrained("yehoshuadiller/my_wnut_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3faef91d6bbe362bbc9c65ce1ec03539c6832b35fe7cc8dc1120f49ed2182375
- Size of remote file:
- 266 MB
- SHA256:
- 88bafc947aa1659f36ded24510e7a77c79d2194ac595000b5e228d5152bc1242
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