Instructions to use Monda/task1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Monda/task1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Monda/task1")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Monda/task1") model = AutoModelForSequenceClassification.from_pretrained("Monda/task1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 91e8053efab04e2024e5c2054b11debc0ddd1c8bafce37fec1eb60a2402c30d8
- Size of remote file:
- 541 MB
- SHA256:
- 23e39946ab99ea3b9a4199f784408c84f39ad27a24c311b20d5e7da615acf5ed
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