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:
- eaa8356f9456e325f47c7ba8c6e98283eaac3d2c2bd3eb09db1e2b6384b919da
- Size of remote file:
- 1.42 GB
- SHA256:
- d210281d3825d8e12df81f11437a886f8286e0b4cdf055132ef04dd61b4792c9
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