Instructions to use ncheng/learning-sentiment with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ncheng/learning-sentiment with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ncheng/learning-sentiment")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("ncheng/learning-sentiment") model = AutoModelForSequenceClassification.from_pretrained("ncheng/learning-sentiment", 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 sha256:5aa7095d79131b61843b63e0af35fc60fa91e299a93de8f853cd8bd56f6182c6
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size 267832560
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