Instructions to use hf-internal-testing/tiny-random-RobertaForMaskedLM with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-RobertaForMaskedLM with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="hf-internal-testing/tiny-random-RobertaForMaskedLM")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-RobertaForMaskedLM") model = AutoModelForMaskedLM.from_pretrained("hf-internal-testing/tiny-random-RobertaForMaskedLM") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 117a1e869f1cdd18c40d34fcf92262356624b5749f8b72e60e27af00ff5140e1
- Size of remote file:
- 357 kB
- SHA256:
- 4ba005994bb7e2911331092a32cc516ddbc96bb1f488474e6bdeb9bc21e1bdf1
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