Instructions to use christopheparisse/complexity_92_reduced_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use christopheparisse/complexity_92_reduced_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="christopheparisse/complexity_92_reduced_model")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("christopheparisse/complexity_92_reduced_model") model = AutoModelForSequenceClassification.from_pretrained("christopheparisse/complexity_92_reduced_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b681dba1ec48b99e3410fa8b12352e25a90648a2c6ecca21cf36b82d10b50fd2
- Size of remote file:
- 553 MB
- SHA256:
- 8962c24bf01bd7d9f4d9ce94ebc194e755f14ed755456b640def736acdc15c55
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