Instructions to use HueyNemud/berties with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use HueyNemud/berties with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="HueyNemud/berties")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("HueyNemud/berties") model = AutoModelForTokenClassification.from_pretrained("HueyNemud/berties", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b8487c5f9131afd7f99af49db362daa2adef6cbff22642a9cf09180f167edba4
- Size of remote file:
- 3.06 kB
- SHA256:
- 31aeb7cf016b0e47597e331fa262b44873f81073521049d8a85dc46bd2004681
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.