Instructions to use a2ran/emotion_classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use a2ran/emotion_classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="a2ran/emotion_classification")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("a2ran/emotion_classification") model = AutoModelForSequenceClassification.from_pretrained("a2ran/emotion_classification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from a2ran/emotion_classification: direct link, hf CLI and curl.
- Browser
- Download file 541 MB
-
https://huggingface.co/a2ran/emotion_classification/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://a2ran/emotion_classification/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/a2ran/emotion_classification/resolve/main/pytorch_model.bin
541 MB
- Xet hash:
- 3c69c18bae01146e1538b00280563f0988dd179f62e8857f47388b686f19a3d7
- Size of remote file:
- 541 MB
- SHA256:
- ec95e6f21d70d02b2777395d0d1159fa879771b5660f352aa5fdeb2744b1f374
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