Instructions to use alistvt/fudnet with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use alistvt/fudnet with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="alistvt/fudnet")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("alistvt/fudnet") model = AutoModelForSequenceClassification.from_pretrained("alistvt/fudnet", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b905722d8404d7c456d76bff691df02771d72436babfe13023e04ababfccf0bd
- Size of remote file:
- 1.88 GB
- SHA256:
- a6770d252272c9777af2f901f1242f2361af8fc8c5e14fd88f0ad1a1c3639479
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