Instructions to use shoubhik/electra_abbv_20k_data_multiclass with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use shoubhik/electra_abbv_20k_data_multiclass with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="shoubhik/electra_abbv_20k_data_multiclass")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("shoubhik/electra_abbv_20k_data_multiclass") model = AutoModelForSequenceClassification.from_pretrained("shoubhik/electra_abbv_20k_data_multiclass", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from shoubhik/electra_abbv_20k_data_multiclass: direct link, hf CLI and curl.
- Browser
- Download file 712 kB
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https://huggingface.co/shoubhik/electra_abbv_20k_data_multiclass/resolve/main/tokenizer.json
- Command line
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hf download hf://shoubhik/electra_abbv_20k_data_multiclass/tokenizer.json
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curl -L -o tokenizer.json https://huggingface.co/shoubhik/electra_abbv_20k_data_multiclass/resolve/main/tokenizer.json
712 kB
File too large to display, you can check the raw version instead.