Instructions to use Cesar42/bert-base-uncased-emotion_v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Cesar42/bert-base-uncased-emotion_v2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Cesar42/bert-base-uncased-emotion_v2")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Cesar42/bert-base-uncased-emotion_v2") model = AutoModelForSequenceClassification.from_pretrained("Cesar42/bert-base-uncased-emotion_v2") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
#2
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:de31347aa943358570f9a03cbdbd9220a0abcddb0ea3c147482d513acd995360
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size 437970952
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