Instructions to use nickmuchi/facebook-data2vec-finetuned-finance-classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nickmuchi/facebook-data2vec-finetuned-finance-classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="nickmuchi/facebook-data2vec-finetuned-finance-classification")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("nickmuchi/facebook-data2vec-finetuned-finance-classification") model = AutoModelForSequenceClassification.from_pretrained("nickmuchi/facebook-data2vec-finetuned-finance-classification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9ee66c02e433404d442bb53896dc1e73b57ef91f442f68ed6e5bb69f349f362a
- Size of remote file:
- 499 MB
- SHA256:
- 04a53b499bc748a36fb1c8ec701b3197ee11be44f3e46896635b7de17375fe4c
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.