Instructions to use gustavolucius/FNClassifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use gustavolucius/FNClassifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="gustavolucius/FNClassifier")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("gustavolucius/FNClassifier") model = AutoModelForSequenceClassification.from_pretrained("gustavolucius/FNClassifier", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 36688c42602cfab122b6dee515a40a2ff04170275b78f49029d9e27588e1c2de
- Size of remote file:
- 268 MB
- SHA256:
- 1919aeeb9db3688d5577db7d04976ed5a80998f26754c48f7fa1e099cd8e4f99
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.