Instructions to use wwells/uncased-w-test with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use wwells/uncased-w-test with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="wwells/uncased-w-test")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("wwells/uncased-w-test") model = AutoModelForSequenceClassification.from_pretrained("wwells/uncased-w-test", 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 sha256:5b7d30ee7e36e06bef390ffca3ab984908bf3b3315cf088d2fcbad12c43391f6
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size 437962832
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