Instructions to use GRPUI/model-667 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use GRPUI/model-667 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="GRPUI/model-667")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("GRPUI/model-667") model = AutoModelForSequenceClassification.from_pretrained("GRPUI/model-667", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- cc90d73c8b7b9c9dbfc812456f3039334052184e31972df48f9e4be4096d2edd
- Size of remote file:
- 2.41 MB
- SHA256:
- 8957dbe6737eb69d96864301fa78722afbb25437be891ea4e4e83f4f726f8e55
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