Instructions to use clem/autonlp-test3-2101787 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use clem/autonlp-test3-2101787 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="clem/autonlp-test3-2101787")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("clem/autonlp-test3-2101787") model = AutoModelForSequenceClassification.from_pretrained("clem/autonlp-test3-2101787", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d19d199bf8ec4cfbc27370b42a2c2c7c604ff151cd3c5ef105bc1af90a5c3ca7
- Size of remote file:
- 2.03 kB
- SHA256:
- 16bf61f9ea9544f9806d6129c0b70d4478b98c26a8397f92bc33b6868f79c054
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.