Instructions to use aimarsg/testlink-class with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use aimarsg/testlink-class with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="aimarsg/testlink-class")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("aimarsg/testlink-class") model = AutoModelForTokenClassification.from_pretrained("aimarsg/testlink-class", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a3d422e345819b8faaa643236f558f3f0b59712e5aa46bef67e0ed0f18b1be42
- Size of remote file:
- 3.58 kB
- SHA256:
- 42dc53289553638897d6879cd95d4eac36cd6b67c2eb83926cd316e44e7da4a6
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.