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:
- b584d6b241fc0d1a8321e5feeb83b4eda46fa8ece5e263a2f0493cddbc9392fb
- Size of remote file:
- 5.47 MB
- SHA256:
- 76c6892bf07a0cd3fc6b348150c440474217f7aba48cfcf7dcf2a93723406126
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