Instructions to use mmine/testwfh with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mmine/testwfh with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="mmine/testwfh")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("mmine/testwfh") model = AutoModelForSequenceClassification.from_pretrained("mmine/testwfh") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 640b27d1fc37b6cc7a0ae5cb8600b21dc16248bec53656e5941034476081f665
- Size of remote file:
- 268 MB
- SHA256:
- e377b886f741181d5c74552e4d2abc07b1330176a0078ff4a96b4b7788c30474
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