Instructions to use tiya1012/emocounterhate with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tiya1012/emocounterhate with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="tiya1012/emocounterhate")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("tiya1012/emocounterhate") model = AutoModelForSequenceClassification.from_pretrained("tiya1012/emocounterhate", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from tiya1012/emocounterhate: direct link, hf CLI and curl.
- Browser
- Download file 268 MB
-
https://huggingface.co/tiya1012/emocounterhate/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://tiya1012/emocounterhate/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/tiya1012/emocounterhate/resolve/main/pytorch_model.bin
268 MB
- Xet hash:
- 0019f564299a8cd11f3707b7e8155e1d2311cd5a6086ff8379c93a878cd055ad
- Size of remote file:
- 268 MB
- SHA256:
- 2c1e33de35c2e8dca62842e153309ae95e277789c3c66778a6cbba0db1da1b43
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