Instructions to use KeiHeityuu/IMCS-DAC-mc-bert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use KeiHeityuu/IMCS-DAC-mc-bert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="KeiHeityuu/IMCS-DAC-mc-bert")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("KeiHeityuu/IMCS-DAC-mc-bert") model = AutoModelForSequenceClassification.from_pretrained("KeiHeityuu/IMCS-DAC-mc-bert") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 57d58c08c98644efed3a57da952901ae4c7105e5ae7bc9995c2be95d92798652
- Size of remote file:
- 409 MB
- SHA256:
- bb8ec1cbf9c3b7e730fc0e7e4286510d8829af155c2b2bec4a58cdef67feffc9
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