Instructions to use annnettte/lettucedect-tool-calling with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use annnettte/lettucedect-tool-calling with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="annnettte/lettucedect-tool-calling")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("annnettte/lettucedect-tool-calling") model = AutoModelForTokenClassification.from_pretrained("annnettte/lettucedect-tool-calling") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 930f57bd52e4eab220d24a85a69838fd87c76184af4c7fb5ebbe8910c6d0c848
- Size of remote file:
- 5.2 kB
- SHA256:
- ca42ded0ed5180bc230482f5c7cb3634b27583e4241346ce7cf9c46aebd18f3f
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.