Instructions to use MarinaTA/FeverCodeChallenge with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use MarinaTA/FeverCodeChallenge with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="MarinaTA/FeverCodeChallenge")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("MarinaTA/FeverCodeChallenge") model = AutoModelForSequenceClassification.from_pretrained("MarinaTA/FeverCodeChallenge", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c3a408065db15dcf45aded03e06ee05b6400d492305e35e2324fcf048b391df0
- Size of remote file:
- 568 MB
- SHA256:
- 2f92f750d82962df414d96645249853739886d1eae14e5e019fd20d16d91f11d
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