Instructions to use tahiyacy/emotion-recognition with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tahiyacy/emotion-recognition with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="tahiyacy/emotion-recognition")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("tahiyacy/emotion-recognition") model = AutoModel.from_pretrained("tahiyacy/emotion-recognition", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from tahiyacy/emotion-recognition: direct link, hf CLI and curl.
- Browser
- Download file 1.13 GB
-
https://huggingface.co/tahiyacy/emotion-recognition/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://tahiyacy/emotion-recognition/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/tahiyacy/emotion-recognition/resolve/main/pytorch_model.bin
1.13 GB
- Xet hash:
- fc82e162cb0ed08b9bec4afd520d13526dfdc4e6d714c6b24436978ad706b959
- Size of remote file:
- 1.13 GB
- SHA256:
- 5fadacdf305c81fa5a0ec391697835875f931e00b602f04d157cd39d6ed532e6
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