Instructions to use hf-tiny-model-private/tiny-random-ConvBertForMaskedLM with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-tiny-model-private/tiny-random-ConvBertForMaskedLM with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="hf-tiny-model-private/tiny-random-ConvBertForMaskedLM")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("hf-tiny-model-private/tiny-random-ConvBertForMaskedLM") model = AutoModelForMaskedLM.from_pretrained("hf-tiny-model-private/tiny-random-ConvBertForMaskedLM", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6bcbb6bd4c84ebf6130f9e8aefdeb359e23e50ee1f8661c95496b1d7575af7e9
- Size of remote file:
- 10.7 MB
- SHA256:
- ff7742ee1fa05ef09ebf42af4c4c0c4f8a2b44776d61654730b86c48b2c73b77
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