Instructions to use pragy10/some_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use pragy10/some_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="pragy10/some_model")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("pragy10/some_model") model = AutoModelForSequenceClassification.from_pretrained("pragy10/some_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2f8d7dcdb11d2a2802d70147f1988deb9ab5c49f62939fe4fd9b1f721f7869f7
- Size of remote file:
- 268 MB
- SHA256:
- 45b3d58fd67ad04b1f4a3b982517f6b94194b31499a20bd6af98445073762dde
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