Instructions to use crcb/emo_go_new with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use crcb/emo_go_new with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="crcb/emo_go_new")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("crcb/emo_go_new") model = AutoModelForSequenceClassification.from_pretrained("crcb/emo_go_new", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1cae831e7c3cdde35eb87905eb8ab42146e81ab50537ebf852d880809d56b139
- Size of remote file:
- 4.08 kB
- SHA256:
- 287fb1cf8d6dc20741b26e4fa20d309dc7ce186bbd49d9e8f56bf5cbef889f50
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