Instructions to use avichr/hebEMO_fear with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use avichr/hebEMO_fear with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="avichr/hebEMO_fear")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("avichr/hebEMO_fear") model = AutoModelForSequenceClassification.from_pretrained("avichr/hebEMO_fear", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from avichr/hebEMO_fear: direct link, hf CLI and curl.
- Browser
- Download file 1.78 kB
-
https://huggingface.co/avichr/hebEMO_fear/resolve/main/training_args.bin
- Command line
-
hf download hf://avichr/hebEMO_fear/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/avichr/hebEMO_fear/resolve/main/training_args.bin
1.78 kB
- Xet hash:
- 873a1eaa2dd5c224b13ef8f5f0e183740c9aa4b76e693bbe578c60ab7952e5de
- Size of remote file:
- 1.78 kB
- SHA256:
- e667b9d39f34abcebf68097fe1f31aca9b5bdff75bd09fba33aa58d6bf49e922
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