Instructions to use dbourget/phil-or-not-2e with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dbourget/phil-or-not-2e with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="dbourget/phil-or-not-2e")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("dbourget/phil-or-not-2e") model = AutoModelForSequenceClassification.from_pretrained("dbourget/phil-or-not-2e", 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:f34395090215e3221f419a958ee98445a84ee531b7e2a3f74fa202c5a1c5f224
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size 1340622760
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