Instructions to use InriaValda/cc_math_bert_ep10 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use InriaValda/cc_math_bert_ep10 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="InriaValda/cc_math_bert_ep10")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("InriaValda/cc_math_bert_ep10") model = AutoModelForMaskedLM.from_pretrained("InriaValda/cc_math_bert_ep10") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ee7cb2e8a293c07f7ebe78ed4637c66c4ba1805e1c4d742f00bc79bd08bb442a
- Size of remote file:
- 534 MB
- SHA256:
- 98ae089edcb1f38e73920de89f0ff4fb494dfd264aff78187b09375fb567fa5d
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