Instructions to use thetkrans/ft_v2_checkpoints with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use thetkrans/ft_v2_checkpoints with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="thetkrans/ft_v2_checkpoints")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("thetkrans/ft_v2_checkpoints") model = AutoModelForSequenceClassification.from_pretrained("thetkrans/ft_v2_checkpoints", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d4ee588631d7c39c56b5362899e0e98d58bbaeb655472dce91b58d3f87aaf798
- Size of remote file:
- 5.2 kB
- SHA256:
- dd62bc3e79276304895acb5a7450d01b04f6ca622b326277166adf4f7d667e52
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