Instructions to use vctmk/mantis-8b-idefics2-classification-tedED-8g_4096_regression with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use vctmk/mantis-8b-idefics2-classification-tedED-8g_4096_regression with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="vctmk/mantis-8b-idefics2-classification-tedED-8g_4096_regression")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForSequenceClassification processor = AutoProcessor.from_pretrained("vctmk/mantis-8b-idefics2-classification-tedED-8g_4096_regression") model = AutoModelForSequenceClassification.from_pretrained("vctmk/mantis-8b-idefics2-classification-tedED-8g_4096_regression", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 129 Bytes
6ee1324 | 1 2 3 4 | version https://git-lfs.github.com/spec/v1
oid sha256:c0494c6d0f196b1b40fae5f61a0c41c131e3b6a2cab5deb3e37d80b57914720e
size 6712
|