Instructions to use BenjaminOcampo/task-implicit_task__model-bert__aug_method-aav 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-aav 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-aav")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("BenjaminOcampo/task-implicit_task__model-bert__aug_method-aav") model = AutoModelForSequenceClassification.from_pretrained("BenjaminOcampo/task-implicit_task__model-bert__aug_method-aav", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from BenjaminOcampo/task-implicit_task__model-bert__aug_method-aav: direct link, hf CLI and curl.
- Browser
- Download file 438 MB
-
https://huggingface.co/BenjaminOcampo/task-implicit_task__model-bert__aug_method-aav/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://BenjaminOcampo/task-implicit_task__model-bert__aug_method-aav/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/BenjaminOcampo/task-implicit_task__model-bert__aug_method-aav/resolve/main/pytorch_model.bin
438 MB
- Xet hash:
- 7326ba8e6dc2f0eb021efaccc401cc2a0f6ac6c1276000cadcefd3cbb79a8ac4
- Size of remote file:
- 438 MB
- SHA256:
- 858d01c8040cc65ecc8465733ccade79937833c23c00fbe46921af792514d2ae
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