Instructions to use NLPinas/EMoBERT-en with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use NLPinas/EMoBERT-en with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="NLPinas/EMoBERT-en")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("NLPinas/EMoBERT-en") model = AutoModelForSequenceClassification.from_pretrained("NLPinas/EMoBERT-en") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
#1
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:a9d23cddb418d38ba7e8f1f8a1f17566605a10b95299fc34d1b4a13a3c607586
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size 498612824
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