Instructions to use alishudi/distil_mlm_act with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use alishudi/distil_mlm_act with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="alishudi/distil_mlm_act")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("alishudi/distil_mlm_act") model = AutoModelForSequenceClassification.from_pretrained("alishudi/distil_mlm_act") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e2aafcb37ca3cf690c27d6d7321a5270cdeaf19009b9e071221e491322f0a044
- Size of remote file:
- 268 MB
- SHA256:
- dc3d7e4ba329824d88c0d03efbdc96cc0e92cd5f3f72b101beca4d517c55e9b1
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