Instructions to use moshew/Mini-bert-distilled with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use moshew/Mini-bert-distilled with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="moshew/Mini-bert-distilled")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("moshew/Mini-bert-distilled") model = AutoModelForSequenceClassification.from_pretrained("moshew/Mini-bert-distilled", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 35fcdf51686b8ea88b3decf569bc70da4fa0eed2a3afadee277cf06fe766f0d4
- Size of remote file:
- 44.9 MB
- SHA256:
- c198c649fdfd3b2b6f6fcdb03b8abf22fbdd77347865c80c3e81231ac1be1b35
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