Instructions to use lukasec/Maverick-Midas with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use lukasec/Maverick-Midas with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="lukasec/Maverick-Midas")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("lukasec/Maverick-Midas") model = AutoModelForSequenceClassification.from_pretrained("lukasec/Maverick-Midas") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7a395eb7254f2b40c344039a744eab80b81ba4aab0529fba95a8f81276ac930b
- Size of remote file:
- 433 MB
- SHA256:
- 5df6d88b2c08450785aa1e6bd6879c3ceebee2f3e0100a0b37b11ac9899e2e89
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