Instructions to use NASA-AIML/MIKA_SafeAeroBERT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use NASA-AIML/MIKA_SafeAeroBERT with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="NASA-AIML/MIKA_SafeAeroBERT")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("NASA-AIML/MIKA_SafeAeroBERT") model = AutoModelForMaskedLM.from_pretrained("NASA-AIML/MIKA_SafeAeroBERT") - Notebooks
- Google Colab
- Kaggle
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README.md
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library_name: transformers
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pipeline_tag: fill-mask
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widget:
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- text: "While flying a fire, the UAS experienced an issue of unknown sorts and
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example_title: "Crashed"
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- text: "During a pre-flight [MASK] run-up, a battery hatch cover disengaged from the fuselage and hit one of the vertical takeoff and landing {VTOL} propellers. The motor failsafe activated and the motors shut down."
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example_title: "Engine"
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library_name: transformers
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pipeline_tag: fill-mask
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widget:
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- text: "While flying a fire, the UAS experienced an issue of unknown sorts and [MASK] to the ground. From the people watching the aircraft near the fire, they seem to think it was some sort of motor failure due to no more noise coming from the aircraft and it falling straight to the ground."
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example_title: "Crashed"
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- text: "During a pre-flight [MASK] run-up, a battery hatch cover disengaged from the fuselage and hit one of the vertical takeoff and landing {VTOL} propellers. The motor failsafe activated and the motors shut down."
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example_title: "Engine"
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