Instructions to use michiel/checkthat_tinybert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use michiel/checkthat_tinybert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="michiel/checkthat_tinybert")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("michiel/checkthat_tinybert") model = AutoModelForSequenceClassification.from_pretrained("michiel/checkthat_tinybert", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0cc721195f4ee1a659f9439472d12ac1614b1c4093696d79490455ea8ad077f2
- Size of remote file:
- 57.4 MB
- SHA256:
- e48ed8ef3c1b256eef31cd5e15ea670e6b365274b6e886c7ffed7c20c1039664
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.