Instructions to use Everlyn/sentiment_model1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Everlyn/sentiment_model1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Everlyn/sentiment_model1")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Everlyn/sentiment_model1") model = AutoModelForSequenceClassification.from_pretrained("Everlyn/sentiment_model1", 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:a50647dab52e146de0d2b71fd8bc6b11fb5b604fa075b27dcfa926d1e7ff04e2
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size 433273844
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