Instructions to use udaypoladi/results with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use udaypoladi/results with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="udaypoladi/results")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("udaypoladi/results") model = AutoModelForSequenceClassification.from_pretrained("udaypoladi/results", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- acb2bfb5ab9c6241efe5b375f2d4740ea02fc93b59bf07fb298abb4b3a9c2d8a
- Size of remote file:
- 5.24 kB
- SHA256:
- 7ec8ae1815d7212e7ac2492426989d6609fd6459d2c09ceb3588a93b3f4e791d
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