Instructions to use wesleyaag/data2vec-emotion-test with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use wesleyaag/data2vec-emotion-test with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="wesleyaag/data2vec-emotion-test")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("wesleyaag/data2vec-emotion-test") model = AutoModelForSequenceClassification.from_pretrained("wesleyaag/data2vec-emotion-test") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
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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 sha256:312c9ea3f815f36f2ac7f7132a1a0ae5ad2bf931c9e226a0fec273259a677d3c
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size 498630520
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