Instructions to use BenjaminOcampo/task-implicit_task__model-bert__aug_method-all 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-all 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-all")# 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-all") model = AutoModelForSequenceClassification.from_pretrained("BenjaminOcampo/task-implicit_task__model-bert__aug_method-all", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from BenjaminOcampo/task-implicit_task__model-bert__aug_method-all: direct link, hf CLI and curl.
- Browser
- Download file 438 MB
-
https://huggingface.co/BenjaminOcampo/task-implicit_task__model-bert__aug_method-all/resolve/refs%2Fpr%2F1/pytorch_model.bin
- Command line
-
hf download hf://BenjaminOcampo/task-implicit_task__model-bert__aug_method-all@refs/pr/1/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/BenjaminOcampo/task-implicit_task__model-bert__aug_method-all/resolve/refs%2Fpr%2F1/pytorch_model.bin
438 MB
- Xet hash:
- 78c923aed9d0bc2050637cf272ea2dca911fd4e7fa7997e2afd1d765774de624
- Size of remote file:
- 438 MB
- SHA256:
- 6d1404a56291537dc7426fe29a58027136caccfdadabbd5a3f1a7770d645c132
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