Instructions to use Forturne/NXR_after_light with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Forturne/NXR_after_light with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Forturne/NXR_after_light")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Forturne/NXR_after_light") model = AutoModelForSequenceClassification.from_pretrained("Forturne/NXR_after_light", 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:d9472c9dac10da726b92f716f7a5eac8e6a5f1a4d6d98e693c0bbb9d0fb3be08
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size 527464172
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