Instructions to use Ibrahim-Alam/Tweet_Sentiment_pos_neg with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Ibrahim-Alam/Tweet_Sentiment_pos_neg with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Ibrahim-Alam/Tweet_Sentiment_pos_neg")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Ibrahim-Alam/Tweet_Sentiment_pos_neg") model = AutoModelForSequenceClassification.from_pretrained("Ibrahim-Alam/Tweet_Sentiment_pos_neg", 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 sha256:8aaf0557446448b6949f5e24fc816e57cdbbadabb74dff8bc7f22c41a65c1cc4
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size 498617024
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