Instructions to use Pendrokar/TorchMoji with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Pendrokar/TorchMoji with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Pendrokar/TorchMoji")# Load model directly from transformers import AutoTokenizer, BertForMultilabelSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Pendrokar/TorchMoji") model = BertForMultilabelSequenceClassification.from_pretrained("Pendrokar/TorchMoji") - Notebooks
- Google Colab
- Kaggle
upload model
Browse files- pytorch_model.bin +3 -0
- vocabulary.json +0 -0
pytorch_model.bin
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version https://git-lfs.github.com/spec/v1
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oid sha256:8cbf6f7067d56aa1c2d571bb169f05fba16cea4c263c06fb3f217f42c591a978
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size 89616062
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vocabulary.json
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