Instructions to use aaulakh/top-level-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use aaulakh/top-level-v2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="aaulakh/top-level-v2")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("aaulakh/top-level-v2") model = AutoModelForSequenceClassification.from_pretrained("aaulakh/top-level-v2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- dd76dc4f36173d05aebb422c3292ad6d92dc2e5d48e40c90a855914f22b7659a
- Size of remote file:
- 268 MB
- SHA256:
- 17ad6b6f017c0e29726f4b3998c72645c86bed9ffc41b0152bd58e6b91c893d3
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