Instructions to use petrichorRainbow/mrf-bert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use petrichorRainbow/mrf-bert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="petrichorRainbow/mrf-bert")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("petrichorRainbow/mrf-bert") model = AutoModelForMaskedLM.from_pretrained("petrichorRainbow/mrf-bert", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 27f9f5dc2c3ece9939041eab6b0ca5c40720eee2b1137c689587df4d929aa610
- Size of remote file:
- 4.02 GB
- SHA256:
- c40d4799fb3a6e7feed0a768db74624b4b8d6999c7bb64354ab0f119d3647468
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