Instructions to use cruiser/roberta-twitter-sentiment-extraction with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use cruiser/roberta-twitter-sentiment-extraction with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="cruiser/roberta-twitter-sentiment-extraction")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("cruiser/roberta-twitter-sentiment-extraction") model = AutoModelForSequenceClassification.from_pretrained("cruiser/roberta-twitter-sentiment-extraction") - 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:e1c68f10f5837912a8ad7b6f44881641fd1210db27300f3d5cf3f67503e2dcd2
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size 328499556
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