Instructions to use billfass/bert-base-sentiment-classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use billfass/bert-base-sentiment-classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="billfass/bert-base-sentiment-classification")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("billfass/bert-base-sentiment-classification") model = AutoModelForSequenceClassification.from_pretrained("billfass/bert-base-sentiment-classification", device_map="auto") - 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:bef7f9c5d727aaf68dc39dfd3d6f66b9d6181e81e61f8b529bb65ec49c30475c
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size 669457728
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