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:
- 467a6e1e5542d3ce0ada6539a2ff0843c3627a24dee5a7895a66cbd326a4c888
- Size of remote file:
- 4.6 kB
- SHA256:
- b54ef7e49f4b95cf975337d339e0359cb86ac5575b311e8983bd14f25259241a
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