Instructions to use nanaaaa/BilingualChildEmo with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nanaaaa/BilingualChildEmo with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="nanaaaa/BilingualChildEmo")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("nanaaaa/BilingualChildEmo") model = AutoModelForSequenceClassification.from_pretrained("nanaaaa/BilingualChildEmo", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
#4
by SFconvertbot - opened
- model.safetensors +3 -0
model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:9afa452c58d70a3eaa6107db688a56ddcd148ced9a4ffeb1dad3c5cafb66b5dc
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size 1112218444
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