Instructions to use Kamer/DayOne5500_Steps with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Kamer/DayOne5500_Steps with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Kamer/DayOne5500_Steps")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Kamer/DayOne5500_Steps") model = AutoModelForSequenceClassification.from_pretrained("Kamer/DayOne5500_Steps", 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:b662e07198ab87284d083059deac12e4137f5ae342ebd2c7cb8eccb1f2fb5b93
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size 438014016
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