Instructions to use research-backup/relbert-roberta-large-iloob-d-semeval2012 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use research-backup/relbert-roberta-large-iloob-d-semeval2012 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="research-backup/relbert-roberta-large-iloob-d-semeval2012")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("research-backup/relbert-roberta-large-iloob-d-semeval2012") model = AutoModel.from_pretrained("research-backup/relbert-roberta-large-iloob-d-semeval2012") - Notebooks
- Google Colab
- Kaggle
add model
Browse files- config.json +1 -1
- pytorch_model.bin +1 -1
config.json
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{
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"_name_or_path": "
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"architectures": [
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"RobertaModel"
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],
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{
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"_name_or_path": "relbert_output/ckpt/iloob_semeval2012/template-d/model",
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"architectures": [
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"RobertaModel"
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],
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pytorch_model.bin
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version https://git-lfs.github.com/spec/v1
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oid sha256:
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size 1421575277
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version https://git-lfs.github.com/spec/v1
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oid sha256:30de844c66e8f866c854dd44393da63d7c1941739682ec070c9d3df542576078
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size 1421575277
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