Instructions to use ManojAlexender/Research_paper_MLM_Final_Label_400k with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ManojAlexender/Research_paper_MLM_Final_Label_400k with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ManojAlexender/Research_paper_MLM_Final_Label_400k")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("ManojAlexender/Research_paper_MLM_Final_Label_400k") model = AutoModelForSequenceClassification.from_pretrained("ManojAlexender/Research_paper_MLM_Final_Label_400k", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 10fb74839675e416737f08bd8b3678da6e4d43477ae967e7e91803b4d1eef91e
- Size of remote file:
- 4.66 kB
- SHA256:
- 09b5cce8c0d25a28570aded432c8d733d16f5ae07da4c42cdd35854f904b3f49
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