Instructions to use tsk-18/results with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tsk-18/results with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="tsk-18/results")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("tsk-18/results") model = AutoModelForSequenceClassification.from_pretrained("tsk-18/results", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ee281dc8784f3a415270393b67b5720e30e7f4d0dc01287bbc2cdf525b4a3b43
- Size of remote file:
- 263 MB
- SHA256:
- 60a532e2f0d0326b96731c8f811a459731c229d37864b71d05f280cc1e6e39f4
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