Instructions to use ThomasLI/efficient_mlm_m0.40-finetuned-classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ThomasLI/efficient_mlm_m0.40-finetuned-classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ThomasLI/efficient_mlm_m0.40-finetuned-classification")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("ThomasLI/efficient_mlm_m0.40-finetuned-classification") model = AutoModelForSequenceClassification.from_pretrained("ThomasLI/efficient_mlm_m0.40-finetuned-classification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1e36fdb49ce833544c2a3a777f3711e8aca6251d00bedde706953f6e508ec64b
- Size of remote file:
- 3.58 kB
- SHA256:
- 37419468ead27c054f4c6f4c80b3cd20086c1c2af8e4cd61ebb982ebfd2ec37e
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