Instructions to use simjo/model1_test with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use simjo/model1_test with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="simjo/model1_test", device_map="auto")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("simjo/model1_test") model = AutoModelForSequenceClassification.from_pretrained("simjo/model1_test", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 75c6df2fd9640a189188b5bd494428f72ab9509771a1b693ce4de8179e31596b
- Size of remote file:
- 443 MB
- SHA256:
- e7378ca87d557618130d61754e24e40cf07117ae0cea57274807903f16c3884c
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.