Instructions to use k0nv1ct/text-complexity with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use k0nv1ct/text-complexity with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="k0nv1ct/text-complexity")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("k0nv1ct/text-complexity") model = AutoModelForTokenClassification.from_pretrained("k0nv1ct/text-complexity", 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 sha256:9c98af0a0dcc4d071581210403a3b70d7ff0c1b226c6354e4d4254cd74fa95c7
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size 435608392
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