Instructions to use nanopass/emotion_test with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nanopass/emotion_test with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="nanopass/emotion_test")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("nanopass/emotion_test") model = AutoModel.from_pretrained("nanopass/emotion_test", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from nanopass/emotion_test: direct link, hf CLI and curl.
- Browser
- Download file 265 MB
-
https://huggingface.co/nanopass/emotion_test/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://nanopass/emotion_test/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/nanopass/emotion_test/resolve/main/pytorch_model.bin
265 MB
- Xet hash:
- d8a74f3d899c0450b053dd573f10275063807bfabdfc3ca44e0e63630d8688ef
- Size of remote file:
- 265 MB
- SHA256:
- d3a458412ffb692c528ca1d76e4164165a57f5d015403b731f4df3cd14ab0d08
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