Instructions to use CPMs/cpm.in.roberta-base.approximate.seed77 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use CPMs/cpm.in.roberta-base.approximate.seed77 with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, RobertaForFactualCounterfactualSequenceClassification tokenizer = AutoTokenizer.from_pretrained("CPMs/cpm.in.roberta-base.approximate.seed77") model = RobertaForFactualCounterfactualSequenceClassification.from_pretrained("CPMs/cpm.in.roberta-base.approximate.seed77", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from CPMs/cpm.in.roberta-base.approximate.seed77: direct link, hf CLI and curl.
- Browser
- Download file 499 MB
-
https://huggingface.co/CPMs/cpm.in.roberta-base.approximate.seed77/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://CPMs/cpm.in.roberta-base.approximate.seed77/pytorch_model.bin
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curl -L -o pytorch_model.bin https://huggingface.co/CPMs/cpm.in.roberta-base.approximate.seed77/resolve/main/pytorch_model.bin
499 MB
- Xet hash:
- e97d9def850782049d52acda17998747cb0b23d43c651237efede3fa698f14f3
- Size of remote file:
- 499 MB
- SHA256:
- edcb5d74319d87f2c70b5bc0b4e888269af981b85b270dc57065810c4522393e
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