Instructions to use MindNetML/dummy-model2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use MindNetML/dummy-model2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="MindNetML/dummy-model2")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("MindNetML/dummy-model2") model = AutoModelForMaskedLM.from_pretrained("MindNetML/dummy-model2") - Notebooks
- Google Colab
- Kaggle
# Load model directly
from transformers import AutoTokenizer, AutoModelForMaskedLM
tokenizer = AutoTokenizer.from_pretrained("MindNetML/dummy-model2")
model = AutoModelForMaskedLM.from_pretrained("MindNetML/dummy-model2")Quick Links
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# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="MindNetML/dummy-model2")