Instructions to use BenjaminOcampo/task-implicit_task__model-bert__aug_method-ri with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use BenjaminOcampo/task-implicit_task__model-bert__aug_method-ri with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="BenjaminOcampo/task-implicit_task__model-bert__aug_method-ri")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("BenjaminOcampo/task-implicit_task__model-bert__aug_method-ri") model = AutoModelForSequenceClassification.from_pretrained("BenjaminOcampo/task-implicit_task__model-bert__aug_method-ri", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from BenjaminOcampo/task-implicit_task__model-bert__aug_method-ri: direct link, hf CLI and curl.
- Browser
- Download file 711 kB
-
https://huggingface.co/BenjaminOcampo/task-implicit_task__model-bert__aug_method-ri/resolve/faeba4bd7b4ec6c7d8adea7885d03dc3dab2030b/tokenizer.json
- Command line
-
hf download hf://BenjaminOcampo/task-implicit_task__model-bert__aug_method-ri@faeba4bd7b4ec6c7d8adea7885d03dc3dab2030b/tokenizer.json
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curl -L -o tokenizer.json https://huggingface.co/BenjaminOcampo/task-implicit_task__model-bert__aug_method-ri/resolve/faeba4bd7b4ec6c7d8adea7885d03dc3dab2030b/tokenizer.json
711 kB
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