Instructions to use encodingai/electra-base-discriminator-im-multilabel-V2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use encodingai/electra-base-discriminator-im-multilabel-V2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="encodingai/electra-base-discriminator-im-multilabel-V2")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("encodingai/electra-base-discriminator-im-multilabel-V2") model = AutoModelForSequenceClassification.from_pretrained("encodingai/electra-base-discriminator-im-multilabel-V2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from encodingai/electra-base-discriminator-im-multilabel-V2: direct link, hf CLI and curl.
- Browser
- Download file 4.73 MB
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https://huggingface.co/encodingai/electra-base-discriminator-im-multilabel-V2/resolve/main/tokenizer.json
- Command line
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hf download hf://encodingai/electra-base-discriminator-im-multilabel-V2/tokenizer.json
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curl -L -o tokenizer.json https://huggingface.co/encodingai/electra-base-discriminator-im-multilabel-V2/resolve/main/tokenizer.json
4.73 MB
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