Instructions to use hf-internal-testing/tiny-random-BertForMaskedLM with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-BertForMaskedLM with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="hf-internal-testing/tiny-random-BertForMaskedLM")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-BertForMaskedLM") model = AutoModelForMaskedLM.from_pretrained("hf-internal-testing/tiny-random-BertForMaskedLM") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e02b3313ee386e19e0e062b1e69953d85b23758b7d1aba0816c6e8eb09f01bbd
- Size of remote file:
- 390 kB
- SHA256:
- cd143bf1dbb2696b40504eeba0ada5a6a90a30594d11bc34008daaba58c7a7ef
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