Instructions to use marcchew/testv4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use marcchew/testv4 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="marcchew/testv4")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("marcchew/testv4") model = AutoModelForSequenceClassification.from_pretrained("marcchew/testv4", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6d389f9982d359c49bedd48d462817710e4740c139e7a2fb35656825fd5407e0
- Size of remote file:
- 5.18 kB
- SHA256:
- c8022ae90dfbd883dbdf680cb04248501f18dd054188cf328dee007b5bbd3933
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