Instructions to use zq2186/model_da_small with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use zq2186/model_da_small with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="zq2186/model_da_small")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("zq2186/model_da_small") model = AutoModelForSequenceClassification.from_pretrained("zq2186/model_da_small", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 272364c8ab045d8edcb7d832aebc9030f8fb283b280645f5bb893c45c7404ad7
- Size of remote file:
- 268 MB
- SHA256:
- 59a6422fb66e38d4e8a5e663af4b3faae8cb5e8944878eca42de423510b98f92
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