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") - Notebooks
- Google Colab
- Kaggle
# Load model directly
from transformers import AutoTokenizer, AutoModelForSequenceClassification
tokenizer = AutoTokenizer.from_pretrained("Forturne/NXR_after_light")
model = AutoModelForSequenceClassification.from_pretrained("Forturne/NXR_after_light")Quick Links
YAML Metadata Warning:empty or missing yaml metadata in repo card
Check out the documentation for more information.
How to use
from transformers import AutoModelForSequenceClassification, AutoTokenizer, pipeline
model = AutoModelForSequenceClassification.from_pretrained("Forturne/NXR_after_light")
tokenizer = AutoTokenizer.from_pretrained("Forturne/NXR_after_light")
pipe = pipeline(model=model, tokenizer=tokenizer)
pipe("ํ์๋ถ ์ฑํจ์ด ์ด๋ป๊ฒ ๋์ธ์?")
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# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Forturne/NXR_after_light")