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:
- 67f909bfcb1b995c925a1e41116b25f2ab21185fa49cf6734ef0535e64f8a826
- Size of remote file:
- 263 MB
- SHA256:
- 5a76c3771b43ca62b9e8d09546768a6cd35048a0a267f3b2485b61d0af8700d1
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