Instructions to use maveriq/mybert-mini-1M with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use maveriq/mybert-mini-1M with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="maveriq/mybert-mini-1M")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("maveriq/mybert-mini-1M") model = AutoModelForMaskedLM.from_pretrained("maveriq/mybert-mini-1M") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f73a48d64fc5d9156e8ae214d9e48061257f79b630a2d58c9eaef190633812a6
- Size of remote file:
- 44.8 MB
- SHA256:
- 6dd61a70f183692606acbc7fd262f6d3d98328ed8b52c2a44281c425c189fc5e
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