Instructions to use CouchCat/ma_sa_v7_distil with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use CouchCat/ma_sa_v7_distil with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="CouchCat/ma_sa_v7_distil")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("CouchCat/ma_sa_v7_distil") model = AutoModelForSequenceClassification.from_pretrained("CouchCat/ma_sa_v7_distil") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 86134af9fbdf48df161876a7b73d463eca9f859ffe1c67b5c9b6beb47e4e156b
- Size of remote file:
- 268 MB
- SHA256:
- 4192a56eae5daa604c1045c8165653c6a854dc636a722aae94bdc902582d769e
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